Classifications

• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
  • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
  • G01C21/20—Instruments for performing navigational calculations
  • G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
  • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
  • G01C21/38—Electronic maps specially adapted for navigation; Updating thereof
  • G01C21/3885—Transmission of map data to client devices; Reception of map data by client devices
  • G01C21/3893—Transmission of map data from distributed sources, e.g. from roadside stations
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
  • G01C5/00—Measuring height; Measuring distances transverse to line of sight; Levelling between separated points; Surveyors' levels
  • G01C5/06—Measuring height; Measuring distances transverse to line of sight; Levelling between separated points; Surveyors' levels by using barometric means
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
  • H04W4/30—Services specially adapted for particular environments, situations or purposes
  • H04W4/33—Services specially adapted for particular environments, situations or purposes for indoor environments, e.g. buildings

Definitions

• Imprecise estimates of the mobile device may have life-or-death consequences for the user of the mobile device since the imprecise altitude estimate can delay emergency personnel response times as they search for the user on multiple floors of a building. In less dire situations, imprecise altitude estimates can lead a user to the wrong area in an environment.
• an estimated altitude of a mobile device is often provided or displayed relative to a frame of reference.
• an altitude relative to Earth’s surface is the height above ellipsoid (HAE) or above mean sea level (AMSL).
• HAE ellipsoid
• AMSL mean sea level
• Other methods of reporting altitude include: i) height above sea-level which is known as Mean Sea Level and is determined by using the geoid (a model of global mean sea level that is used to measure precise surface elevations), ii) height above terrain (HAT) which is determined using a terrain database, and iii) floor number, which is often most useful for a user, especially when inside a structure.
• Mean Sea Level a model of global mean sea level that is used to measure precise surface elevations
• HAT height above terrain
• floor number which is often most useful for a user, especially when inside a structure.
• a method involves selecting a set of altitude envelope distribution constraints for a physical building.
• a set of altitude envelope distributions for the physical building is generated in accordance with the set of altitude envelope distribution constraints, each altitude envelope distribution comprising one or more first altitude envelopes, and each of the first altitude envelopes corresponding to a respective estimated floor number of the physical building.
• An aggregate altitude envelope distribution is generated for the physical building using the set of altitude envelope distributions and in accordance with the set of altitude envelope distribution constraints, the aggregate altitude envelope distribution comprising one or more second altitude envelopes, each of the one or more second altitude envelopes corresponding to a respective estimated floor number of the physical building.
• a reference altitude is determined for the physical building, and an absolute aggregate altitude envelope distribution is determined using the reference altitude and the aggregate altitude envelope distribution, the aggregate altitude envelope distribution comprising one or more third altitude envelopes, each of the third altitude envelopes corresponding to a respective estimated floor number of the physical building.
• a system includes one or more servers that are operable to select a set of altitude envelope distribution constraints for a physical building, and generate a set of altitude envelope distributions for the physical building in accordance with the set of altitude envelope distribution constraints.
• Each altitude envelope distribution comprises one or more first altitude envelopes, each of the first altitude envelopes corresponding to a respective estimated floor number of the physical building.
• An aggregate altitude envelope distribution for the physical building is generated using the set of altitude envelope distributions and in accordance with the set of altitude envelope distribution constraints, the aggregate altitude envelope distribution comprising one or more second altitude envelopes, where each of the one or more second altitude envelopes corresponds to a respective estimated floor number of the physical building.
• a reference altitude of the physical building is determined, and an absolute aggregate altitude envelope distribution is determined using the reference altitude and the aggregate altitude envelope distribution, the aggregate altitude envelope distribution comprising one or more third altitude envelopes, where each of the one or more third altitude envelopes corresponds to a respective estimated floor number of the physical building.
• FIG. 1 shows a simplified operational environment for estimating a building floor number and/or a floor label of a mobile device, in accordance with some embodiments.
• FIG. 2 shows a simplified example of building models that correspond to a physical building of FIG. 1, in accordance with some embodiments.
• FIG. 3 shows a table of example altitude envelope ranges, in accordance with some embodiments.
• FIG. 4 shows a table of example distributions of altitude envelope ranges, in accordance with some embodiments.
• FIG. 5 shows a table of example aggregate altitude envelope values, in accordance with some embodiments.
• FIGS. 6-13 show graphical representations of example aggregate altitude envelope distributions, in accordance with some embodiments.
• FIG. 14 shows a simplified example of a portion of a process for determining an aggregate altitude distribution, in accordance with some embodiments.
• FIG. 15 simplified example of a portion of a process for estimating a building floor number based on an estimated altitude, in accordance with some embodiments.
• FIG. 16 shows a graphical representation of an example absolute aggregate altitude envelope distribution, in accordance with some embodiments.
• FIG. 17 includes a simplified example of a portion of a process for estimating a building floor number based on an estimated altitude, in accordance with some embodiments.
• FIG. 18 shows a graphical representation of an example absolute aggregate altitude envelope distribution, in accordance with some embodiments.
• FIG. 19 includes a simplified example of a portion of a process for estimating a building floor number based on an estimated altitude, in accordance with some embodiments.
• FIG. 20 shows a graphical representation of an example absolute aggregate altitude envelope distribution, in accordance with some embodiments.
• FIG. 21 includes a simplified example of a portion of a process for mapping floor numbers to floor labels, in accordance with some embodiments.
• FIG. 22 includes a simplified example of a portion of a process for estimating a building floor number based on an estimated altitude, in accordance with some embodiments.
• FIG. 23 shows a simplified top-down view of an operational environment, in accordance with some embodiments.
• FIG. 24 shows simplified implementations of transmitters, mobile devices, and servers of the operational environment shown in FIG. 1, in accordance with some embodiments.
• mapped estimated building floor designators may be added to a database for later retrieval. Upon retrieval, the estimated building floor designators may be used to convert an estimated altitude of a mobile device to an estimated floor number and/or floor label.
• a floor designator that indicates which floor of the building the user is on may be significantly more useful to first responders trying to reach the user as compared to receiving a raw estimated altitude value reported by the user’s mobile device.
• estimated building floor designators include estimated building “floor numbers” and/or estimated building “floor labels”.
• the floor numbers and floor labels are referred to as being “estimated” because they may be largely determined computationally as compared to being determined based on a physical survey of a building.
• crowd-sourced and surveyed data may be included in the mapped data and thus some of the mapped estimated building floor designators may be mapped based on user or surveyor provided data. The selection of which floor designator to use can come from either estimated values, mapped values, or a combination of the two.
• a floor label is distinct from a floor number.
• the distinction is drawn because floor labels as observed by a user may not reflect the true floor number count (e.g., counting from the ground up) and can vary from country -to- country and morphology-to-morphology.
• the floor label “1st Floor” corresponds to a ground-level floor and the floor label “2nd Floor” corresponds to a first floor above the ground level.
• the floor label “1st Floor” corresponds to the first floor above the ground level floor
• “Ground Floor” corresponds to the ground level.
• the ground floor is labeled “RC” for “Rez-de-chausee”, which is the French phrase for the ground floor.
• the floor label “13th Floor” is often omitted owing to the stigma associated with the number 13, despite there actually being a 13th floor.
• any floor label containing the number 4 is omitted in some countries or cultures owing to the stigma associated with the number 4, despite there actually being floor numbers 4, 24, 34, 40, and so on.
• FIG. 1 shows a simplified operational environment 100 for estimating a floor number and/or floor label of a mobile device, in accordance with some embodiments.
• the operational environment includes a first building 190, a second building 191, mobile devices 120a-e, satellites 150, a network of terrestrial transmitters HOa-b, and servers 130. Also shown are positioning signals 153 from the satellites 150, positioning signals 113a-b from the respective transmitters HOa-b, altitude designators altitude 1 through n + 1, and communication and command signals associated with the servers 130.
• building floor labels may vary from building- to-building.
• the building 190 includes floors labeled, in order of lowest to highest, “Floor LI”, “Ground Floor”, “First Floor”, and “Penthouse”.
• the building 191 includes floors labeled, in order of lowest to highest, “Parking Garage”, “First Floor”, and “Second Floor”.
• the mobile device 120b and the mobile device 120e are both at altitude level Altitude 2
• the mobile device 120b and the mobile device 120e are both at street level in their respective buildings
• the mobile device 120b is on a building floor labeled “Ground Floor”
• the mobile device 120e is on a building floor labeled “First Floor”.
• Each of the transmitters 1 lOa-b and the mobile devices 120a-e may be located at different altitudes or depths that are inside or outside various natural or manmade structures (e.g., the buildings 190/191), relative to different terrain.
• the positioning signals 113a-b and 153 are respectively transmitted from the transmitters 1 lOa-b and satellites 150, and are subsequently received by the mobile device 120 using known transmission technologies. Though only two terrestrial transmitters are shown for simplicity, it is understood that the network of terrestrial transmitters 110a- b may include many more than two transmitters. Similarly, although only one satellite is shown for simplicity, it is understood that the satellites 150 may include many more than one satellite.
• the transmitters 1 lOa-b may transmit the signals 113a-b using one or more common multiplexing parameters that utilize time slots, pseudorandom sequences, frequency offsets, or other approaches, as is known in the art or otherwise disclosed herein.
• the mobile devices 120a-e may take different forms, including a mobile phone or another wireless communication device, a portable computer, a navigation device, a tracking device, a receiver, or another suitable device that can receive the signals 113a-b and/or 153. Examples of possible components in the transmitters 1 lOa-b, the mobile device 120, and the server 130 are shown in FIG. 24 and discussed below.
• each transmitter 1 lOa-b and mobile device 120a-e may include atmospheric sensors (e.g., atmospheric pressure, temperature, and/or humidity sensors, weather stations, etc.) for generating measurements of atmospheric conditions (e.g., atmospheric pressure and temperature) that are used to estimate an unknown altitude of the mobile devices 120a-e.
• atmospheric sensors e.g., atmospheric pressure, temperature, and/or humidity sensors, weather stations, etc.
• atmospheric conditions e.g., atmospheric pressure and temperature
• altitude can be computed using a measurement of pressure from a calibrated pressure sensor of a mobile device along with ambient pressure measurement(s) from a network of calibrated reference pressure sensors and a measurement of ambient temperature from the network or other source.
• An estimate of an altitude of a mobile device can be computed by the mobile device, a server, or another machine that receives needed information as follows: (Equation 1), where Pmobiie is the estimate of pressure at the location of the mobile device by a pressure sensor of the mobile device, Psensor is an estimate of pressure at the location of a reference pressure sensor that is accurate to within a tolerated amount of pressure from true pressure (e.g., less than 5 Pa), Tremote is an estimate of temperature (e.g., in Kelvin) at the location of the reference pressure sensor or a different location of a remote temperature sensor, hsensor is an estimated altitude of the reference pressure sensor that is estimated to within a desired amount of altitude error (e.g., less than 1.0 meters), g corresponds to the acceleration due to gravity (e.g., -9.8 m/s 2 ), R is a gas constant, and M is the molar mass of air (e.g., dry air or other).
• Equation 1 Pmobiie is the
• the estimate of pressure at the location of the reference pressure sensor can be converted to an estimated reference-level pressure that corresponds to the reference pressure sensor in that it specifies an estimate of pressure at the latitude and longitude of the reference pressure sensor, but at a reference-level altitude that likely differs from the altitude of the reference pressure sensor.
• the reference-level pressure can be determined as follows: where Psensor is the estimate of pressure at the location of the reference pressure sensor, Pref ix the reference-level pressure estimate, and h re f is the reference-level altitude.
• the altitude of the mobile device h mob n e can be computed using Equation 1, where h re f is substituted for hsensor and Pref is substituted for Psensor.
• the reference-level altitude h re f may be any altitude and is often set at mean sea-level (MSL).
• MSL mean sea-level
• the reference-level pressure estimates are combined into a single reference-level pressure estimate value (e.g., using an average, weighted average, or other suitable combination of the reference pressures), and the single reference-level pressure estimate value is used for the reference-level pressure estimate Pref
• a building model that corresponds to a physical building is computationally constructed of individual “stacked” floors. That is, a building model is “constructed” by computationally determining vertical boundaries and/or offsets for each floor of a building model and accumulating those vertical boundaries and/or offsets.
• the term “building floor number” is taken to mean the level in a building, not the actual surface upon which a user will stand.
• the physical space the user could possibly occupy on a floor is referred to herein as an “altitude envelope” which is bounded by the lowest surface of the floor (i.e., the “ground” of that floor) and the ceiling of that floor, with the bounds separated by a ground-to- ceiling separation.
• An altitude envelope of a first floor is “stacked” on top of or below that of a second floor with an appropriate intervening floor/ceiling separation value (a “boundary thickness”) by logically and or mathematically associating the first floor and the second floor.
• the boundary thickness can be a thickness of the floor or a thickness of the ceiling, depending on a chosen convention.
• a building model having two stacked floors may have a building model height value that is equal to the cumulative height of each of the floors.
• a building model having two stacked floors may have a building height value that is just equal to the height of the topmost stacked floor if the lowest floor is modeled as a basement.
• altitude envelopes of each floor of a building model are stacked on top of either a lowest starting point of the building model or on top of that of another floor.
• each floor of a building model is stacked below either a highest starting point of the building model or below another floor.
• Each floor includes a vertical distance called a floor-to-floor separation.
• the floor-to-floor separation includes a ground-to-ceiling separation of the floor as well as the boundary thickness.
• FIG. 2 shows a simplified example 200 of building models 290a and 290b that correspond to a physical building (e.g., the building 190 of FIG. 1), in accordance with some embodiments.
• a first building model 290a includes floors 220a-d, boundary thickness values 206a-d, ground-to-ceiling separation values 202a- d, and floor-to-floor separation values 204a-d.
• a second building model 290b includes floors 220e-h, boundary thickness values 206e-h, ground-to-ceiling separation values 202e-h, and floor-to-floor separation values 204e-h.
• Floors labeled Floor 0 are assumed to be subterranean.
• the ground surface of the floor 220b labeled Floor 1 of the building model 290a is assumed to align vertically with a top surface of the terrain.
• the ground surface of the floor 220f labeled Floor 1 of the building model 290b is assumed to be offset from a top surface of the terrain by a boundary thickness value 206e labeled Boundary thickness'.
• the floor-to-floor separation values are assumed to be uniform throughout a building model. In other embodiments, the floor-to-floor separation values are assumed to be non-uniform in some or all portions of a building model. For example, a floor-to-floor separation value may be larger for a subset of floors (e.g., when modeling the lobby of a hotel).
• boundary thickness values are assumed to be uniform throughout a building model. In other embodiments, the boundary thickness values are assumed to be non-uniform in some, or all, portions of a building model. For example, a boundary thickness value may be larger for a subset of floors, such as when modeling the ceiling above a lobby, the floor below a large meeting room, etc.
• the boundary thickness value at the top of a building model (also known as the roof thickness) (e.g., 206d and 206h) can also be larger than the boundary thickness value in the rest of the building model.
• Attics are generally located above a top floor of a building but below the roof. Attics often do not have horizontally flat ceilings and are bounded by the roof and the floor/ceiling thickness above the top floor. Crawl spaces are small areas that have little vertical clearance that typically sit below a building and are used to run wiring, cables, pipes, etc.
• an additional floor with a typically smaller maximum floor-to-ceiling separation value is added near the top of the estimated floors.
• a building database provides statistics on a building’s height, such as maximum height (corresponding to the very top of the roof) or minimum height (corresponding to the roof line, or the lowest point of a roof)
• a difference above a threshold e.g. 2 meters
• the calculated difference could then be used to determine if it is likely that the roof is sloped and thus may contain an attic space. This may be more typical of residences than businesses.
• a building database does not provide a minimum and maximum building height, then the given height of the building could be either minimum / maximum, or some metric in between, such as a mean or median.
• a building database may then be inferred whether the provided height corresponds to the maximum or minimum height based on building morphology, architectural trends, building codes (i.e., city rules), building information, or other information.
• a particular building is 5 m tall
• the building could either have two levels (2.5 m each) with a flat roof, or may be a single story house with a floor-to- ceiling separation of 3-3.5 m and an 1.5-2 m attic.
• the building is located in a suburban area, such as San Jose, and neighboring homes are known to be single story, or if building codes mandate only single story homes, etc.
• the 5 m height can be assumed to be roof maximum and not roof line.
• neighboring homes are known to have multiple levels, or if the building in question is known to be an apartment complex with units that imply multiple levels (i.e. Unit 101, Unit 201), then the 5 m height can be assumed to be roof line and hence a two level building.
• an additional subterranean vertical separation is added near the bottom of the estimated floors.
• the additional subterranean vertical separation is typically no more than 1 m, for example, in order to model crawl spaces when constructing the estimated floor numbers.
• Such embodiments could be architecturally based, with details of a building’s foundation used to infer the existence of a crawl space (e.g. a house on a concrete slab likely has no crawl space).
• Other embodiments could use building footprints to determine if an attic or crawl space is present in a building.
• Other embodiments may be market-based, with some markets like New La likely not having subterranean features owing to flood risk. Some markets may be dominated by peaked rooftops (to protect against snow), and other markets may be dominated by flat rooftops, which can be used to infer if an attic is likely.
• Each floor of a building model is associated with one or more altitude envelopes.
• An altitude envelope is a range of altitudes bounded by an altitude envelope minimum and an altitude envelope maximum and corresponds to the bounds on where a user of a mobile device could physically be located on each floor of a physical building, assuming they cannot be inside a floor or ceiling.
• a “floor of interest” is the maximum floor number considered, and a given floor’s boundary thickness is above the floor-to-ceiling separation.
• Altitude Envelope Minimum (floor-to-floor separation X (floor number - 1)
• Altitude Envelope Maximum loor-to- loor separation X floor number (Equation 8), where boundary thickness' is a boundary thickness value above the terrain (e.g., boundary thickness value 206e shown in FIG. 2).
• altitude envelope ranges can be defined as follows, assuming counting begins at floor number
• a “floor of interest” is the maximum floor number considered
• a given floor’s boundary thickness is above the floor-to-ceiling separation
• the boundary thickness’ is a boundary thickness value above the terrain (e.g., boundary thickness value 206e in FIG. 2).
• FIG. 3 An example table 300 of altitude envelope ranges determined for each floor of a four-story building model is shown in FIG. 3, in accordance with some embodiments.
• the values of the table 300 were generated assuming a uniform 0.3 m boundary thickness for the building model and a uniform 3 m floor-to- floor separation using equation 3 and equation 4, where the floor-to-floor separation is equal to the 0.3 m boundary thickness plus a 2.7 m floor-to-ceiling separation and the ground of the lowest non-subterranean floor is aligned with a top surface of the terrain.
• the aggregate altitude envelope distribution is a series of altitude ranges (“altitude envelopes”), where each altitude range corresponds to altitudes associated with a particular floor of a physical building.
• altitude envelopes Such a “distribution” in this sense is a representation of how altitude envelopes correspond to sequential floor numbers of a building.
• An example table 400 shown in FIG. 4 shows two distributions, “Distribution 1”, and “Distribution 2” of altitude envelope ranges determined computationally for a four-story building model, in accordance with some embodiments.
• Altitude envelope minimum and altitude envelope maximum values of Distribution 1 in the table 400 were calculated using equation 3 and equation 4 using a uniform floor-to-ceiling separation value of 2.2 m and a boundary thickness of 0.3 m (i.e., a floor-to-floor separation value of 2.5 m).
• Values of Distribution 2 were calculated using equation 3 and equation 4 using a uniform floor-to-ceiling separation value of 2.7 m and a boundary thickness of 0.3 m (i.e., a floor-to-floor separation value of 3 m).
• altitude envelope distributions are created for a wide range of floor-to-floor separation values.
• a set of altitude envelope distributions may be created by generating an altitude envelope distribution for each floor-to-floor separation value beginning with a minimum expected floor-to-ceiling separation value, such as 2.5 m, and incrementing the floor-to-floor separation value by a uniform value, such as 0.1 m, until a maximum expected floor-to-floor separation value, such as 4.5 m, is reached.
• the floor-to-floor separation value may be incremented by a uniform value, as described, or by a non-uniform value.
• the floor-to-floor separation value may be log-spaced, have repeated separations, or may be weighted on particular separation values. For example, instead of incrementing floor-to-floor separation values by a uniform value of .1 m until 4.5 m is reached, e.g., 2.5 m, 2.6 m, 2.7 m ... 4.5 m, in some embodiments the floor-to-floor separation values are incremented at an increasing rate, e.g., 2.5 m, 2.6 m, 2.8 m, 3.5 m, . . .4.5 m.
• the floor-to-floor separation value remain fixed for multiple distributions to provide a greater weight to that separation value in the aggregate altitude envelope distribution, e.g., 2.5 m, 2.5 m, 2.5 m,...4.5 m.
• the set of altitude envelope distributions is then filtered to remove altitude envelope distributions that result in non-physical (e.g., physically impossible, improbably, or impractical) floors or building models.
• distributions that are filtered from the set of altitude envelope distributions do not contribute to an aggregate altitude envelope distribution.
• distributions that are filtered from the set of altitude envelope distributions do not fully contribute to an aggregate altitude envelope distribution (e.g., their contribution is weighted such that they contribute less to the aggregate altitude envelope distribution as compared to distributions that were not filtered from the set of altitude envelope distributions). Any remaining altitude envelope distributions are then combined to create an aggregate altitude envelope distribution.
• the aggregate altitude envelope distribution is created for a building model by determining an aggregate altitude envelope minimum and an aggregate altitude maximum for each floor of the building model.
• each of the altitude envelopes is determined as a probability distribution function (uniform, Gaussian/normal, or some other distribution), and when combined into an aggregate altitude envelope distribution, the aggregate altitude envelope distribution may resemble a probability distribution with a peak that corresponds to the peak of the combination of the weighted altitude envelopes. For example, with reference to FIG.
• an aggregate altitude envelope distribution 606 may have floor distributions that are weighted more toward the lower end (i.e., the Floor 1 range from 606 is concentrated more from 0-2.2 m than from 2.2-2.7 m).
• the aggregate altitude minimum for a floor is the smallest altitude envelope minimum value of altitude envelopes associated with that floor for each of the altitude envelope distributions.
• the aggregate altitude maximum for a floor is the largest altitude envelope maximum value of altitude envelopes associated with that floor for each of the altitude envelope distributions.
• An example aggregate altitude envelope distribution constructed according to this embodiment is shown in a floor number lookup table 500 of FIG. 5.
• the aggregate altitude envelope minimum value for each floor is the minimum altitude envelope value from Distribution 1 or Distribution 2 for that floor as shown in table 400 of FIG. 4.
• the aggregate altitude envelope maximum value for each floor is the maximum altitude envelope value from Distribution 1 or Distribution 2 for that floor as shown in table 400 of FIG. 4.
• the aggregate altitude minimum is within a percentage (e.g., 10%) of the altitude envelope minimum value of altitude envelopes associated with that floor number for each of the altitude envelope distributions.
• the aggregate altitude maximum is within a percentage (e.g., 10%) of the largest altitude envelope maximum value of altitude envelopes associated with that floor number for each of the altitude envelope distributions.
• each of the altitude envelopes is determined as a probability distribution function.
• probability distribution functions can be concentrated (peaked) where there is significant overlap across altitude envelope distributions corresponding to different floor-to-floor separation values, and the aggregate altitude envelope distribution can be concentrated in regions where there are multiple altitude envelope distributions overlapping.
• the aggregate altitude envelope distribution can be combined from Distribution 1 and Distribution 2, where the aggregate altitude envelope distribution can be concentrated between 9 m and 9.7 m, and less concentrated between 7.5 m and 9 m, and less concentrated between 9.7 m and 11.7 m.
• FIG. 6 An example graphical representation 600 of the altitude envelope distribution values of table 400 and the resulting aggregate altitude envelope distribution values of the floor number lookup table 500 is shown in FIG. 6, in accordance with some embodiments.
• the graph 600 includes a first altitude envelope distribution 602, a second altitude envelope distribution 604, boundary thicknesses 622a-f, an aggregate altitude envelope distribution 606, and a legend 610 of floor numbers that includes altitude envelope ranges for floors 1-4, each floor being designated by a unique fill pattern.
• the altitude envelope ranges for each floor of the first distribution 602 correspond to the values for Distribution 1 shown in table 400 of FIG. 4.
• the altitude envelope ranges for each floor of the second distribution 604 correspond to the values for Distribution 2 shown in table 400 of FIG. 4.
• the boundary thicknesses 622a-f are set to a fixed value of 0.3 m. As shown by the dashed lines, minimum altitude envelope values and maximum altitude envelope values from the first altitude envelope distribution 602 and the second altitude envelope distribution 604 are selected to create the aggregate altitude envelope distribution 606.
• values of the aggregate altitude envelope distribution 606 are stored as a floor number lookup table for later retrieval. For example, upon estimating which physical building a mobile device is in, an aggregate altitude envelope distribution, i.e., a floor number lookup table, associated with that physical building may be retrieved. In some embodiments, if there is uncertainty as to which physical building the mobile device is in, multiple aggregate altitude envelope distributions may be retrieved, each of the distributions corresponding to a physical building that the mobile device is likely to be in. Then, the retrieved aggregate altitude envelope distribution(s) can be used to map an estimated altitude of the mobile device to a floor number and/or floor label for each of the physical building(s).
• an estimated altitude of 7 m could be translated, or “mapped” to floor number 3. Since there can be overlapping altitude envelopes regions, multiple floor numbers could also be selected. For example, an altitude of 8 m could indicate floor number 3 OR floor number 4, OR floor number 3 (with an indicated 75% likelihood) OR floor number 4 (with an indicated 25% likelihood), with the percentages reflecting the confidence of the result. In some embodiments, the confidence of each result is derived as the distance to the floor number centroid. Further descriptions of determining and summarizing estimated floor numbers and their associated confidences are described below.
• floor numbers are precomputed (as detailed below) along with their respective ranges once and then used to populate a database for subsequent lookup going forward, the values only being recalculated if the constraints change (buildings are further constructed or demolished, database errors are determined and/or rectified, etc.).
• FIG. 7 Another example of an aggregate altitude envelope distribution constructed using a set of altitude envelope distributions is shown in FIG. 7, in accordance with some embodiments.
• a small boundary thickness has been assumed.
• Basement floors/levels are not illustrated, but the same approaches disclosed herein are applicable for buildings having single or multiple levels below ground level.
• FIG. 7 includes a graph 700 that shows a set of altitude envelope distributions 702, an aggregate altitude envelope distribution 704 that was generated using the altitude envelope distributions 702, and a legend 710 of floor numbers.
• the altitude envelope distributions 702 include individual altitude envelope distributions that each correspond to a different floor-to- floor separation value ranging from 2.5 m to 4.5 m.
• no altitude envelope distribution constraints described in detail below, have been applied to the altitude envelope distributions 702.
• the higher floors of the aggregate altitude envelope distribution 704 have an increasingly wider altitude envelope range as compared to the lower floors.
• floor #7 floor number 7
• the aggregated altitude envelope distribution 704 spans from about 17 to 32 meters. Such a wide span makes it unlikely that using values from the aggregate altitude envelope distribution 704 as a floor number lookup table to generate an estimated floor number using an estimated altitude will result in an accurate or useful result.
• specific factual information about a physical building is available (e.g., from a data source such as a building database). Such information may include the actual number of floors in that building, the actual height of that building, and so on. However, in many instances, only general, regional, information is available (e.g., a maximum building height for a region, a maximum number of floors for a region, etc.). Without any information about a physical building, it may be assumed that the floor number 1, as defined herein, is on the ground, meaning that the Altitude Envelope Min of floor number 1 has a 0 m height- above-terrain value, possibly including any boundary thickness.
• altitude envelope distribution constraints include a minimum building height, a maximum building height, a minimum floor height, a maximum floor height, a minimum number of floors, and a maximum number of floors.
• altitude envelope distribution constraints may be selected, each with varying quality. These distributions may be determined considering: 1) using no constraints, 2) constraining the number of stories (which may or may not include the number of basement stories), 3) constraining the building height (which may or may not include the depth of the building into the ground), and 4) using both of the preceding constraints.
• the selected constraints are optionally used when generating the altitude envelope distributions and/or are optionally used to filter out any altitude envelope distributions that violate one or more of the constraints.
• boundary thicknesses can be estimated or can be based on measured data.
• FIG. 8 shows a simplified graphical representation 800 of altitude envelope distribution values and the resulting aggregate altitude envelope distribution values, in accordance with some embodiments.
• the graph 800 includes the first altitude envelope distribution 602 from FIG. 6, the second altitude envelope distribution 604, the boundary thicknesses 622a-f, a third altitude envelope distribution 808, boundary thicknesses 822g-i, the aggregate altitude envelope distribution 606, and a legend 810 of floor numbers.
• the third altitude envelope distribution 808 was generated using 4 m floor-to-floor separation values, and the boundary thicknesses 622a-f and 822g-i are set to a fixed value of 0.3 m.
• Basement floors/levels are not illustrated, but the same approaches disclosed herein are applicable for buildings having single or multiple levels below ground level.
• an altitude envelope distribution may be constrained by a minimum or maximum number of floors in a building.
• the maximum number of floors may be based on general information for the region that the physical building is located in.
• the process for determining altitude envelopes for each floor of a building is halted when the maximum number of floors is reached.
• an altitude envelope distribution constraint on the number of floors in the building i.e., four was used when generating the distributions 602, 604, and 808, and an altitude envelope distribution constraint on maximum building height (i.e., 12 m) was applied after the distributions 602, 604, and 808 were generated.
• the third altitude envelope distribution 808 has a non-physical floor (i.e., floor number 4).
• Floor number 4 of the third altitude envelope distribution 808 is considered to be non-physical because it has an altitude envelope that is only a little more than half a meter high and is, therefore, an improbable floor configuration for a building. Because the distribution 808 has a non-physical floor, altitude values from that distribution were advantageously excluded when the aggregate altitude envelope distribution 606 was determined. If the building height constraint had not been applied to the distributions 602, 604, and 808, the third altitude envelope distribution 808 would have also contributed to the aggregate altitude envelope distribution 606.
• selecting altitude envelope distribution constraints includes a sub-step of validating a set of initially selected constraints.
• the set of initially selected altitude envelope distribution constraints may be validated before being used when generating the altitude envelope distributions and/or before applying the constraints to the generated altitude envelope distributions.
• a given building height constraint is valid given the morphology of the region (e.g., suburban, where no building exceeds a threshold, such as 20 m), or given a maximum building height for the region (e.g., no building in Chicago is taller than a region’s tallest building, such as the Willis Tower in Chicago).
• a constraint on the number of building stories is valid given a morphology of the region (e.g., suburban, where no building exceeds 5 stories, for example), or given a maximum number of building stories for the region (e.g., no building has more stories than the building in the region with the most stories).
• combinations of altitude envelope distribution constraints may also be validated. For example, some combinations of constraints may result in non-physical building models when a particular floor-to- floor separation value and/or floor-to-ceiling separation value is assumed. For example, if an absolute minimum floor-to-floor separation value of 2 m is assumed (which is reasonable, assuming an upper bound of people’s heights), then a combination of a first altitude envelope distribution constraint requiring that the building have eight stories and a second altitude envelope distribution constraint requiring a 10 m building height would result in a non-physical building model because each story would only be 1.25 m tall. In another example, if a maximum floor-to-floor separation of 5 m is assumed, then a 100 m building with 10 stories would be non-physical because each resulting story is only half as high as suggested by the building height.
• non-physical constraints Several options for handling individual or combinations of altitude envelope distribution constraints for a particular building that do not pass validation (“non-physical constraints”) are disclosed herein. Each of such options can be performed together or separately and include: i) Removing the building height constraint. This may be performed if the building height constraint is determined to be erroneous or improbable for the region that the building is in (e.g., a suburban house that is 100 m tall is improbable, a skyscraper height that exceeds the tallest skyscraper in the world is improbable, etc.); ii) Removing the maximum floor number constraint.
• FIG. 9 shows an example of aggregate altitude envelope distribution constructed using just a constraint on a maximum number of floors in the building (e.g., because the building height constraint was removed or because a building height constraint is unavailable), in accordance with some embodiments.
• a small boundary thickness has been assumed and the lowest altitude of the altitude envelope for floor number 1 is aligned with a building height of 0 m (i.e., the floors are stacked from the bottom up).
• FIG. 9 includes a graph 900 that shows a set of altitude envelope distributions 902, an aggregate altitude envelope distribution 904 that was generated using the altitude envelope distributions 902, and a legend 910 of floor numbers.
• Basement floors/levels are not illustrated, but the same approaches disclosed herein are applicable for buildings having single or multiple levels below ground level.
• the altitude envelope distributions 902 include individual altitude envelope distributions that each correspond to a different floor-to- floor separation value ranging from 2.5 m to 4.5 m.
• the distributions 902 were constructed given a constraint that the building being modeled has a maximum of eight floors.
• FIG. 10 shows an example of aggregate altitude envelope distribution constructed using just a constraint on a maximum building height (e.g., because the maximum number of floors constraint was removed or because the maximum number of floors is not available), in accordance with some embodiments. Similar to the example shown in FIG. 9, in this example, a small boundary thickness has been assumed and the lowest altitude of the altitude envelope for floor number 1 is aligned with a building height of 0 m (i.e., the floors are stacked from the bottom up).
• FIG. 10 shows an example of aggregate altitude envelope distribution constructed using just a constraint on a maximum building height (e.g., because the maximum number of floors constraint was removed or because the maximum number of floors is not available), in accordance with some embodiments. Similar to the example shown in FIG. 9, in this example, a small boundary thickness has been assumed and the lowest altitude of the altitude envelope for floor number 1 is aligned with a building height of 0 m (i.e., the floors are stacked from the bottom up).
• FIG. 10 includes a graph 1000 that shows a set of altitude envelope distributions 1002, an aggregate altitude envelope distribution 1004 that was generated using the altitude envelope distributions 1002, and a legend 1010 of floor numbers.
• Basement floors/levels are not illustrated, but the same approaches disclosed herein are applicable for buildings having single or multiple levels below ground level.
• the distributions 1002 were initially constructed without a constraint on a maximum number of floors and each distribution corresponds to a different floor-to-floor separation value ranging from 2.5 m to 4.5 m. However, after a constraint on a maximum building height of 20 m was applied, a subset of the distributions 1002, illustrated as rectangles with dashed lines, were filtered from the set of distributions 1002 because they resulted in non-physical floors (not shown) at the top of the building. For example, a topmost floor of a building having a floor-to- ceiling separation that was less than 2.5 m is a non-physical floor. As such, the subset of the distributions 1002 that are represented by dashed lines were not used to generate the aggregate altitude envelope distribution 1004.
• floors may be computationally stacked from the building rooftop down.
• distributions having floor separations that yield non-physical floors at the bottom of the building e.g., floor-to-floor separations less than 2.5 m for bottom floors
• distributions that are computationally stacked from the building rooftop down could extend into the ground and not be removed based on the non-physical constraint.
• FIG. 11 includes a graph 1100 that shows a set of altitude envelope distributions 1102, an aggregate altitude envelope distribution 1104 that was generated using the altitude envelope distributions 1102, and a legend 1110 of floor numbers.
• Basement floors/levels are not illustrated, but the same approaches disclosed herein are applicable for buildings having single or multiple levels below ground level.
• the distributions 1102 were initially constructed without a constraint on a maximum number of floors and each corresponds to a different floor-to-floor separation value ranging from 2.5 m to 4.5 m. However, after a constraint on a maximum building height of 20 m was applied, a subset of the distributions 1102, illustrated as rectangles with dashed lines, were filtered from the set of distributions 1102 because they resulted in non-physical floors (not shown) at the bottom of the building (e.g., a bottommost floor had a floor-to-ceiling separation that was less than 2.5 m). As such, the subset of the distributions 1102 that are represented by dashed lines were not used to generate the aggregate altitude envelope distribution 1104.
• two altitude envelope distribution constraints may be combined to reduce the number of possible altitude envelope distributions even more than the individual constraints.
• An example of an aggregate altitude envelope distribution constructed using a set of altitude envelope distributions when a maximum floor number constraint and a maximum building height constraint are applied is shown in FIG. 12, in accordance with some embodiments. Similar to that shown in FIG. 10, in this example, a small boundary thickness has been assumed and the lowest altitude of the altitude envelope for floor number 1 is aligned with a building height of 0 m (i.e., the floors are computationally stacked from the bottom up).
• FIG. 12 An example of an aggregate altitude envelope distribution constructed using a set of altitude envelope distributions when a maximum floor number constraint and a maximum building height constraint are applied is shown in FIG. 12, in accordance with some embodiments. Similar to that shown in FIG. 10, in this example, a small boundary thickness has been assumed and the lowest altitude of the altitude envelope for floor number 1 is aligned with a building height of 0 m (i
• FIG. 12 includes a graph 1200 that shows a set of altitude envelope distributions 1202, an aggregate altitude envelope distribution 1204 that was generated using the altitude envelope distributions 1202, and a legend 1210 of floor numbers.
• Basement floors/levels are not illustrated, but the same approaches disclosed herein are applicable for buildings having single or multiple levels below ground level.
• the distributions 1202 were initially constructed using a constraint on a maximum number of floors (i.e., a maximum of 6 floors) and each distribution corresponds to a different floor-to-floor separation value ranging from 2.5 m to 4.5 m. However, after a constraint on a maximum building height of 20 m was applied, a subset of the distributions 1202, illustrated as rectangles with dashed lines, were filtered from the set of distributions 1202 because they resulted in non-physical floors (not shown) at the top of the building (e.g., a topmost floor had a floor-to-ceiling separation that was less than 2.5 m).
• the subset of the distributions 1202 that are represented by dashed lines were not used to generate the aggregate altitude envelope distribution 1204.
• the combination of two altitude envelope distribution constraints advantageously results in much less overlap between the altitude envelopes of the aggregate altitude envelope distribution 1204 as compared to the aggregate altitude envelope distribution 1104 of FIG. 11, the aggregate altitude envelope distribution 1004 of FIG. 10, and especially the aggregate altitude envelope distribution 904 of FIG. 9.
• a building floor number lookup table that uses the aggregate altitude envelope distribution 1204 will be more accurate than a building floor lookup table that uses the aggregate altitude envelope distributions 1104, 1004, or 904.
• a building floor number lookup table that uses the aggregate altitude envelope distribution 1204 may be advantageously generated without a costly survey of the associated physical building while still providing accurate estimated floor numbers for that building based on a user’s estimated altitude.
• floors may be computationally stacked from the building rooftop down and floor separations that yield non-physical floors at the bottom of the building (e.g., floor-to-floor separations less than 2.5 m for bottom floors) may be removed.
• floor separations that yield non-physical floors at the bottom of the building (e.g., floor-to-floor separations less than 2.5 m for bottom floors) may be removed.
• An example of an aggregate altitude envelope distribution constructed using a set of altitude envelope distributions when a maximum floor number constraint and a maximum building height constraint are applied is shown in FIG. 13, in accordance with some embodiments. Similar to that shown in FIG.
• FIG. 13 includes a graph 1300 that shows a set of altitude envelope distributions 1302, an aggregate altitude envelope distribution 1304 that was generated using the altitude envelope distributions 1302, and a legend 1310 of floor numbers.
• Basement floors/levels are not illustrated, but the same approaches disclosed herein are applicable for buildings having single or multiple levels below ground level.
• the distributions 1302 were initially constructed using a constraint on a maximum number of floors (i.e., a maximum of 6 floors) and each distribution corresponds to a different floor-to-floor separation value ranging from 2.5 m to 4.5 m. However, after a constraint on a maximum building height of 20 m was applied, a subset of the distributions 1302, illustrated as rectangles with dashed lines, were filtered from the set of distributions 1302 because they resulted in non-physical floors (not shown) at the bottom of the building (e.g., a bottommost floor had a floor-to- ceiling separation that was less than 2.5 m).
• the subset of the distributions 1302 that are represented by dashed lines were not used to generate the aggregate altitude envelope distribution 1304.
• the combination of two altitude envelope distribution constraints advantageously results in much less overlap between the altitude envelopes of the aggregate altitude envelope distribution 1304 as compared to the aggregate altitude envelope distribution 1104 of FIG. 11, the aggregate altitude envelope distribution 1004 of FIG. 10, and especially the aggregate altitude envelope distribution 904 of FIG. 9.
• a building floor number lookup table that uses the aggregate altitude envelope distribution 1304 will be more accurate than a building floor lookup table that uses the aggregate altitude envelope distributions 1104, 1004, or 904.
• the aggregate altitude envelope distribution may include a combination of altitude envelope distributions that were generated using different techniques.
• a bottom portion of an aggregate altitude envelope distribution may include altitude envelope distributions that were formed from the bottom up (e.g., as shown and described with reference to FIG. 12)
• a top portion of the aggregate altitude envelope distribution may include altitude envelope distributions that were formed from the top down (e.g., as shown and described with reference to FIG. 13) to further decrease altitude envelope overlap.
• a top half of an aggregate envelope distribution may include the top half of the aggregate envelope distribution 1304 corresponding to floor numbers 4-6, and a bottom half of the altitude envelope distribution may include the bottom half of the aggregate altitude distribution 1204 corresponding to floor numbers 1-3.
• the middle floor of the building could be a combination of the 1204 and 1304 at the middle floor, either by taking the minimum from 1204 and the maximum from 1304, the maximum from 1304 and the minimum from 1204, or some other combination.
• FIG. 14 A simplified example of a portion of a process 1400 for determining an aggregate altitude distribution is shown in FIG. 14, in accordance with some embodiments.
• the particular steps, order of steps, and combination of steps are shown for illustrative and explanatory purposes only. Other embodiments can implement different particular steps, orders of steps, and combinations of steps to achieve similar functions or results.
• each step of the process 1400 is carried out at a server (e.g., the server(s) 130 of FIG. 1) and/or at a mobile device (e.g., in the vicinity of a mobile device 120a-e of FIG. 1).
• the processes for generating a mapping of estimated floor numbers to estimated floor labels for a building may be used independently of other processes disclosed herein.
• a set of altitude envelope distribution constraints are selected for a physical building that a floor number lookup table is being constructed for (e.g., such as that shown in FIG. 5).
• altitude envelope distribution constraints include a minimum building height, a maximum building height, a minimum floor height, a maximum floor height, a minimum number of floors, and a maximum number of floors.
• the set of altitude envelope distribution constraints includes one or more of such constraints. In other embodiments, no constraints are used and the set of constraints is an empty set.
• the set of altitude envelope distribution constraints are selected by, or using, the server(s) 130 based on user provided settings (e.g., a configuration setting), constraint availability from a database, the quality of data in a relevant database (e.g., a building and/or terrain database), or a provided design or tolerance criteria.
• the set of altitude envelope distribution constraints are automatically selected by, or using, the server(s) 130 based on an iterative process of trying various constraints to generate an optimized outcome (e.g., an aggregate altitude envelope distribution with minimal overlap between altitude envelopes).
• step 1402 includes a sub-step of validating a set of initially selected constraints.
• the set of initially selected constraints may be validated using general information about building morphology for the region that the physical building is located in. As was described above, such validation includes determining if any of the constraints are improbable given the morphology of buildings in the region that the physical building is located in.
• each of the altitude distributions includes one or more stacked altitude envelopes, each altitude envelope corresponding to a building floor number of the physical building and being separated from another altitude envelope, or from an initial point, by a floor-to-floor separation value, or a floor-to-ceiling separation value plus a boundary thickness value.
• each of the altitude envelope distributions in the set is determined using a different floor-to-floor separation value, or floor-to-ceiling separation value, that ranges from a minimum value (e.g., 2.5 m) to a maximum value (e.g., 4.5 m).
• the set of altitude envelope distributions included the distributions 602, 604, and 808, where the distribution 602 corresponds to a 2.5 m floor-to-floor separation value, the distribution 604 corresponds to a 3 m floor-to-floor separation value, and the distribution 808 corresponds to a 4 m floor-to-floor separation value. Also in the example shown in FIG.
• the first altitude envelope distribution constraint i.e., selected at step 1402 was a constraint on a maximum number of floors that is equal to four floors.
• each of the distributions 602, 604, and 808 were constructed so as to only include a maximum number of four floors.
• the initial set of altitude envelope distributions may be determined by stacking altitude envelopes with a fixed floor-to- floor separation value, such as 3 m, until the height of the building is met or exceeded. While this approach is simple, it may be sensitive to error accumulation, especially at higher floors.
• the initial set of altitude envelope distributions for a building may be determined by dividing the height of a building by the number of floors therein, provided that both values are known (e.g., from a building database). For example, an 8 m building with two floors likely has a ground floor having an altitude envelope spanning 0 m to 4 m from the bottom of the building, and a top floor having an altitude envelope spanning 4 to 8 m.
• such calculated altitude envelopes would have clearly delineated boundaries that do not overlap with each other, and may not properly characterize a user that is close to the boundary value.
• a user altitude of 4.001 m would be assigned to the top floor of the building (having an altitude envelope that spans 4 to 8 m) without reflecting that the user is 0.001 m from the boundary of the ground floor.
• the first embodiment advantageously enables a wide-range of floor separation values to be considered and for non-physical floor-to-floor separation values (i.e., improbably short floors based on human height) to be filtered from the altitude envelope distribution. Additionally, the first embodiment, as disclosed herein, advantageously allows for non-uniform floor-to-floor separation values. In contrast to the latter two embodiments, the first embodiment, as disclosed herein, advantageously allows for a buffer of floor ranges to be generated (i.e. floor ranges that overlap), which can be used to determine when a user's altitude could confidently be assigned to one or more adjacent floors in addition to the determined floor.
• floor ranges having an overlap advantageously improve floor number estimation as compared to a simple approach having no overlap. For example, a user elevation of 4.001 m would be mapped to potentially being at the ground floor or the top floor of the building, as opposed to the simple approach which would only assign the user position to the top floor.
• the user’s elevation of 4.001 m were noisy and happened to fluctuate by a few millimeters, the user’s floor number would jump around between the ground floor and the top floor of the building, as opposed to some embodiments disclosed herein that specify both of the overlapping floors.
• the user’s elevation also had a determined confidence/uncertainty of 4.5 m +/- 0.4 m, then the overlap between the user’s elevation range of 4.1 m to 4.9 m could indicate the ground floor or the top floor, as opposed to the simple approach which would still indicate only the top floor, resulting in a noisy floor number estimation and poor user experience.
• a second one or more of the selected altitude envelope distribution constraints is applied to the set of altitude envelope distributions to filter the set of altitude envelope distributions.
• the second altitude envelope distribution constraint i.e., selected at step 1402 is a constraint on a maximum building height that is equal to 20 m.
• the distribution 808 is filtered from the set of aggregate altitude envelope distributions and is thereafter not used to generate the aggregate altitude envelope distribution 606.
• the remaining set of altitude envelope distributions is used to determine an aggregate altitude envelope distribution.
• the remaining set of altitude envelope distributions is the same as the initial set of altitude envelope distributions generated at step 1404.
• the remaining set of altitude envelope distributions is the same as the initial set of altitude envelope distributions determined at step 1404.
• an absolute aggregate altitude envelope distribution is generated using the aggregate altitude envelope distribution.
• altitude values of the absolute altitude envelope distribution are each an absolute altitude value with respect to a reference frame, such as a height- above-ellipsoid, which is the height above the Earth ellipsoid.
• a reference altitude value such as height-above-ellipsoid altitude value of the lowest floor.
• the reference altitude value of the lowest floor can be determined in numerous ways, including: a) Querying a terrain database within the building footprint and averaging the result across the building footprint. Alternatively, the minimum or maximum terrain or some other statistical metric may be used; and/or b) Querying a terrain database outside the building footprint (out to some buffer like 10 m) and averaging the results. This is beneficial for terrain databases that may not sufficiently handle building removal in their modeling. Alternatively, the minimum or maximum terrain or some other statistical metric may be used.
• the minimum terrain would likely indicate the altitude of the ground of the lowest floor; and/or c) Querying a building database, if available, to retrieve the reference altitude value of the lowest floor directly.
• the absolute aggregate altitude envelope distribution, and optionally the (relative) aggregate altitude envelope distribution are stored for immediate or later use.
• the absolute aggregate altitude envelope distribution is stored as a floor number lookup table at a database and in association with the physical building (e.g., by address, building name or designator, and/or coordinates or as part of a larger data structure).
• a mapping of estimated floor numbers to estimated floor labels is optionally generated. Details of step 1414 are described below with reference to FIG. 21.
• the floor number lookup table can be used, e.g., by a server and/or a mobile device, to estimate which floor of a physical building that a mobile device is on by using an estimated altitude of the mobile device and the absolute aggregate altitude envelope distribution.
• altitude data e.g., from a mobile device
• the processes and techniques disclosed herein for i) determining an aggregate altitude envelope distribution, ii) mapping an estimated altitude (and optionally an altitude uncertainty/confidence), of a mobile device to a floor number using an altitude envelope distribution, and iii) reporting the mapped floor number to an endpoint may be used in conjunction or independently of one another. That is, an aggregate altitude envelope distribution determined using the techniques and processes disclosed herein may be used with an alternative process (i.e., as compared to those disclosed herein) for mapping an estimated altitude (and optionally an altitude uncertainty/confidence) of a mobile device to a floor number using an altitude envelope distribution, and/or an alternative process for reporting the mapped floor number to an endpoint.
• the techniques and processes for mapping an estimated altitude (and optionally an altitude uncertainty/confidence) of a mobile device to a floor number using an altitude envelope distribution as disclosed herein may be used with an alternative process for determining an aggregate envelope distribution and/or an alternative process for reporting the mapped floor number to an endpoint.
• the techniques and processes for reporting the mapped floor number to an endpoint disclosed herein may be used with an alternative process for determining an aggregate altitude envelope distribution and/or an alternative process for mapping an estimated altitude of a mobile device to a floor number using an altitude envelope distribution.
• FIG. 15 includes a simplified example of a portion of a process 1500 that may be used as a first embodiment of step 1412 of FIG. 14 for using an absolute aggregate altitude envelope distribution to estimate a building floor number based on an estimated altitude of a mobile device.
• the particular steps, order of steps, and combination of steps are shown for illustrative and explanatory purposes only. Other embodiments can implement different particular steps, orders of steps, and combinations of steps to achieve similar functions or results.
• each step of the process 1500 is carried out at a server (e.g., the server(s) 130 of FIG. 1) and/or at a mobile device.
• the processes 1500 for using an absolute aggregate altitude envelope distribution to estimate a building floor number based on an estimated altitude (and optionally an altitude uncertainty/confidence) of a mobile device may be used in conjunction with, or independently of, other processes disclosed herein.
• the steps of process 1500 are described with reference to the example graph 1600 of FIG. 16 that includes an absolute altitude envelope distribution 1606, a legend 1610, and estimated altitudes 1630a-b, in accordance with some embodiments.
• it may be uncertain which building a mobile device is in.
• the steps of the process 1500 are performed for each building within a list of possible buildings that the mobile device may be located within. In other embodiments, if the buildings are of similar distributions, the distributions may be combined.
• an estimated altitude of a mobile device is identified (e.g., either of 1630a or 1630b).
• an estimated altitude of the mobile device may be determined based on measurements of atmospheric pressure made by a barometric pressure sensor of the mobile device and/or using positioning signals received at the mobile device.
• the estimated altitude may be an estimated altitude received at a server from the mobile device.
• the estimated altitude may be retrieved from a server, or from another source.
• the entire altitude estimation process may be performed at the mobile device.
• step 1504 for each floor number of the absolute altitude envelope distribution, if the estimated altitude is within an altitude envelope corresponding to that floor number, that floor number is added to a list of estimated floor numbers.
• the list of estimated floor numbers would only include floor number 4.
• the list of estimated floor numbers would include both floor number 4 and floor number 3 because the estimated altitude 1630b is within the altitude envelope corresponding to floor number 4 as well as within the altitude envelope corresponding to floor number 3 based on the overlap thereof.
• the list of estimated floor numbers is returned to an endpoint such as a user of the mobile device, a first responder, a computer system, a server, and/or a device that initiated the process 1500.
• FIG. 17 includes a simplified example of a portion of a process 1700 that may be used as a second embodiment of step 1412 of FIG. 14 for using the absolute aggregate altitude envelope distribution to estimate a building floor number based on an estimated altitude.
• the particular steps, order of steps, and combination of steps are shown for illustrative and explanatory purposes only. Other embodiments can implement different particular steps, orders of steps, and combinations of steps to achieve similar functions or results.
• each step of the process 1700 is carried out at a server (e.g., the server(s) 130 of FIG. 1) and/or at a mobile device.
• the processes 1700 for using an absolute aggregate altitude envelope distribution to estimate a building floor number based on an estimated altitude (and optionally an altitude uncertainty/confidence) of a mobile device may be used in conjunction with, or independently of, other processes disclosed herein.
• the steps of the process 1700 are performed for each building within a list of possible buildings that the mobile device may be located within.
• an estimated altitude of a mobile device is identified (e.g., 1830).
• the estimated altitude may be an estimated altitude determined using a mobile device that is inside of a building that corresponds to the absolute altitude envelope distribution.
• the estimated altitude may be an altitude value retrieved from a server or from another source.
• a vertical central tendency (e.g., 1852a-d) is calculated for the altitude envelope that corresponds to that floor.
• each vertical central tendency is a mean or median of the corresponding altitude envelope.
• the vertical central tendency for an altitude envelope may be calculated as follows: (Equation 11).
• a distance magnitude between the estimated altitude and the vertical central tendency is calculated for each altitude envelope of the absolute altitude envelope distribution.
• the distance magnitude (e.g., 1840, 1842) is calculated for an altitude envelope by determining the absolute value of a difference between the estimated altitude value (e.g., 1830) and the central tendency of that altitude envelope (e.g., 1852d, 1852c).
• step 1708 for each floor number of the absolute altitude envelope distribution, that floor number is conditionally added to a list of estimated floor numbers based on the distance magnitude for the altitude envelope of that floor number.
• Conditionally adding the floor number to the list of estimated floor numbers involves adding the floor number to the list of estimated floor numbers based on one or more specified conditions. If the condition is met, the floor number is added to the list of estimated floor numbers. If the condition is not met, the floor number is not added to the list of estimated floor numbers. For example, in some embodiments, a floor number is added to the list of estimated floor numbers if the distance magnitude is the smallest distance magnitude as compared to the distance magnitudes corresponding to the other floor numbers. In such embodiments, all other floor numbers are excluded from the list of estimated floor numbers. In other embodiments, a floor number is added to the list of estimated floor numbers if the floor number’s corresponding distance magnitude is less than a given threshold (e.g., 5 meters).
• a given threshold e.g., 5 meters
• all other floor numbers are excluded from the list of estimated floor numbers.
• all of the floor numbers are added to the list of estimated floor numbers and the list of estimated floor numbers is ordered by distance magnitude along with confidences that map from the distance magnitude.
• the list of estimated floor numbers may also include the distance magnitude value corresponding to each of the estimated floor numbers.
• the list of estimated floor numbers may only include floor number 4 because the distance magnitude 1840 is less than the distance magnitude 1842.
• the list of estimated floor numbers may only include floor number 4 if the distance magnitude 1840 is less than a threshold value and the distance magnitude 1842 is greater than the threshold value.
• the list of estimated floor numbers may include all of the floor numbers, and it would be ordered from the smallest distance magnitude to the largest distance magnitude (i.e., floor number 4, floor number 3, floor number 2, and then floor number 1).
• the list of estimated floor numbers and/or floor labels is returned to an endpoint (e.g., to a server, mobile device, and/or device that initiated the process 1700).
• FIG. 19 includes a simplified example of a portion of a process 1900 that may be used as a third embodiment of step 1412 of FIG. 14 for using the absolute aggregate altitude envelope distribution to estimate a building floor number based on an estimated altitude.
• the particular steps, order of steps, and combination of steps are shown for illustrative and explanatory purposes only. Other embodiments can implement different particular steps, orders of steps, and combinations of steps to achieve similar functions or results.
• each step of the process 1900 is carried out at a server (e.g., the server(s) 130 of FIG. 1) and/or at a mobile device.
• the processes 1900 for using an absolute aggregate altitude envelope distribution to estimate a building floor number based on an estimated altitude (and optionally an altitude uncertainty/confidence) of a mobile device may be used in conjunction with, or independently of, other processes disclosed herein.
• it may be uncertain which building a mobile device is in.
• the steps of the process 1900 are performed for each building within a list of possible buildings that the mobile device may be located within.
• the distributions may be combined.
• estimated altitude data of a mobile device is identified (e.g., 2030).
• the estimated altitude data includes an estimated altitude and an uncertainty/ confidence interval corresponding to the estimated altitude, usually represented as X +/- Y m, though the interval may also be asymmetric (+Y m, -Z m).
• the estimated altitude data 2030 includes an estimated altitude 2030 which is represented by a dot, and a corresponding confidence interval 2031 which is represented by whiskers centered at the dot.
• the estimated altitude data may be received from a mobile device. In other situations, the estimated altitude data may be retrieved from a server or another source.
• a lower bound of the altitude data is calculated as follows, where the estimated altitude confidence value is half of an estimated altitude confidence interval when the confidence interval is symmetrical, or a portion of the estimated altitude confidence interval when the confidence interval is asymmetrical:
• the confidence interval, or estimated altitude confidence value is determined or calculated as described in U.S. Patent No. 10,655,961, issued May 19, 2020 and/or U.S. Patent Application No. 17/447,027, filed September 7, 2021, both of which are incorporated herein in their entirety.
• the confidence interval, or estimated altitude confidence value is already calculated by another process.
• the confidence interval, or estimated altitude confidence value is a fixed value.
• an altitude overlap value between the altitude data and the altitude envelope that corresponds to that floor is calculated.
• the altitude data as described herein includes an estimated altitude value and optionally includes an altitude uncertainty/confidence value associated with the estimated altitude.
• the altitude overlap value for a given floor may include a vertical span (e.g., 5m) or an overlap percentage (e.g., 10%) for which an altitude range between the Lower Bound of Equation 12 and the Upper Bound of Equation 13 overlaps with an altitude range between an altitude envelope minimum value and altitude envelope maximum value for that floor.
• the confidence interval 2031 overlaps the altitude envelope of floor number 4 by the first altitude overlap value 2040.
• the confidence interval 2031 overlaps the altitude envelope of floor number 3 by the second altitude overlap value 2042.
• step 1906 for each floor number of the absolute altitude envelope distribution, that floor number is added to a list of estimated floor numbers based on the calculated overlap value for that floor number.
• a floor number is added to the list of estimated floor numbers if the calculated altitude overlap value for that floor is the largest calculated altitude overlap value as compared to the calculated altitude overlap values corresponding to the other floor numbers. In such embodiments, all other floor numbers are excluded from the list of estimated floor numbers.
• a floor number is added to the list of estimated floor numbers if the floor number’s corresponding calculated altitude overlap value is greater than a given percentage threshold (e.g., 20%) or a distance range (e.g., 3 m) when measured relative to either the altitude envelope range or the mobile device’s estimated altitude range.
• a given percentage threshold e.g. 20%
• a distance range e.g. 3 m
• all other floor numbers are excluded from the list of estimated floor numbers.
• all of the floor numbers are added to the list of estimated floor numbers and the list of estimated floor numbers is ordered by their respective calculated altitude overlap values.
• the list of estimated floor numbers may also include the associated confidence interval of the estimated altitude data.
• the list of estimated floor numbers may also include the associated confidence interval or uncertainty for each of the floor numbers.
• the list of estimated floor numbers is returned to an endpoint (e.g., to a server, mobile device, and/or device that initiated the process 1900).
• a list of rules for the removal and addition of floor labels is first compiled.
• Such lists can be geographic-specific, morphology-specific, or building type-specific.
• the list of rules could specify that all buildings within a geofence in downtown San Francisco do not have a “floor 13”.
• the list could specify that buildings in Montreal’s postal codes have “Ground Floors” as the bottom floor, and the 1st floor is directly above the Ground Floor.
• the list of rules could specify that buildings above 10 meters tall in Beijing lack all floor labels with “4” in them.
• the list or rules could combine multiple rules. Such lists of rules can be augmented with specific exceptions, such as particular buildings that are known to follow a different pattern or have a predefined floor label scheme.
• a building can have the north side that includes a bedroom and hallway, and the south side that includes an attic space. In such cases, the 2D position of the user becomes important in determining floor labels.
• FIG. 21 shows a portion of process 2100 that is an example embodiment of step 1414 shown in FIG. 14 to optionally generate a mapping of estimated floor numbers to estimated floor labels for the building, in accordance with some embodiments.
• the particular steps, order of steps, and combination of steps are shown for illustrative and explanatory purposes only. Other embodiments can implement different particular steps, orders of steps, and combinations of steps to achieve similar functions or results.
• each step of the process 2100 is carried out at a server (e.g., the server(s) 130 of FIG. 1) and/or at a mobile device.
• the processes for generating a mapping of estimated floor numbers to estimated floor labels for a building may be used in conjunction with, or independently of, other processes disclosed herein.
• each estimated floor number of an absolute aggregate altitude distribution of a building is mapped to identically named estimated floor labels (e.g., by a server).
• floor number 1 is mapped to “floor number 1” or “first floor”
• floor number 2 is mapped to “floor number 2” or “second floor”, and so on.
• map”, “mapped”, “mapping”, and “translate”, in this context means to logically, descriptively, and/or programmatically associate one or more items to one or more other items (e.g., in a database, dataset, or other data object).
• step 2104 floor labels are flagged or removed from the mapping based on regional and/or cultural criteria. For example, the “13th floor”, “4th floor”, “39th floor”, may be considered to be “unlucky” in some cultures.
• step 2104 involves assembling, identifying, or retrieving a list of rules (e.g., from a server) that may be regionally specific or include a building-to-building context. Such rules are similar to those described above, e.g., buildings in San Francisco may not have a “13 th floor”. Floor labels are then removed from the mapping based on those rules.
• rules e.g., from a server
• step 2106 it is determined if there is a sufficient number of floor labels (i.e., there is at least one available floor label for each floor number). If it is determined that there is a sufficient number of floor labels, flow continues to step 2108.
• step 2108 new floor labels are added to the mapping at appropriate places (e.g., “Lobby”, “Mezzanine”, “Observatory”) (e.g., by a server).
• step 2108 involves assembling, identifying, or retrieving a list of rules that may be regionally specific or be on a building-to-building context (e.g., from a server). Such rules are similar to those described above, e.g., buildings in Montreal may have a “Ground Floor”. Floor labels are then added to the mapping based on those rules.
• the estimated floor numbers are aligned to the estimated floor labels and excess estimated floor labels are discarded (e.g., by a server).
• An excess number of floor labels is the inverse problem of having an insufficient number of floor labels as determined at step 2106. For example, if the estimated floor label “13 th floor” was removed from the mapping, then the estimated floor number 13 would be aligned to the floor label “14 th floor”.
• a building database includes all possible residential unit numbers
• the format of such residential unit numbers could be interpreted as the possible floor labels.
• the floor labels could use the first digit of the apartment numbers to establish floor labels 1 and 2 for such a complex.
• an additional source of floor labels e.g., a list of elevator buttons from all elevator banks in a building, or a list of floors from building plans
• such information may be used by the server to establish floor labels.
• the process 2100 is advantageously performed by one or more servers that are operable to access and operate on large datasets.
• step 2106 If it was determined at step 2106 that the amount of floor labels is less than the number of floor numbers, flow continues to step 2112 where the number of floor labels is incremented by one or more. Flow then returns to step 2102 for reprocessing with a larger buffer of possible floor labels.
• FIG. 22 shows a portion of process 2200, which is an example embodiment of step 1412 shown in FIG. 14, in accordance with some embodiments.
• the particular steps, order of steps, and combination of steps are shown for illustrative and explanatory purposes only. Other embodiments can implement different particular steps, orders of steps, and combinations of steps to achieve similar functions or results.
• each step of the process 2200 is carried out at a server (e.g., the server(s) 130 of FIG. 1) and/or at a mobile device.
• a portion of the process 2200 is described with reference to graph 2300 shown in FIG. 23, in accordance with some embodiments.
• the graph 2300 provides a simplified top-down view of an operational environment which includes a centroid 2302 of an estimated position of a mobile device, a confidence 2304 of the estimated position that forms a radius of a 2D (two-dimensional) confidence region 2306, a first building polygon 2308, a second building polygon 2310, and a third building polygon 2312.
• a building polygon is at least a two-dimensional top-down outline of a physical building. Building polygons may be stored and retrieved from a building, terrain, or topology dataset, as is known in the art. Also shown are overlap regions 2320, 2321, and 2322.
• the overlap regions 2320, 2321, and 2322 are each defined by the overlapped portion of that region’s respective building polygon and the interior of the confidence region 2306.
• the 2D confidence region 2306 is a uniform density distribution (e.g., normally distributed, or other distribution).
• the 2D confidence region 2306 adheres to a non-uniform distribution, such as a weighted distribution having greater weights closer to the centroid 2302 and lesser weights farther from the centroid 2302.
• two overlapping building footprints having the same area of overlap e.g., 10%
• a region of overlap that is closer to the centroid 2302 may be weighted more than a similarly sized region of overlap that is farther from the centroid 2302.
• the applied overlap region weights could then be used when the overlap regions are being sorted to determine which building the mobile device is most likely within.
• the first building polygon 2308 corresponds to a building located at “123 Main Street”, or identified by name or designator (e.g., “Empire State Building”, “Building 1”, “Al”, etc.), that is 50 m tall, has 17 stories, has a 2.5% overlap at overlap region 2320 with the 2D confidence region 2306, and has a nearest distance of 1.41 units to the centroid 2302. That is, 2.5% of the 2D confidence region 2306 overlaps with the first building polygon 2308.
• name or designator e.g., “Empire State Building”, “Building 1”, “Al”, etc.
• the second building polygon 2310 corresponds to a building located at “234 Main Street” that is 30 m tall, has 9 stories, has a 7.3% overlap region 2321 with the 2D confidence region 2306, and has a nearest distance of 1 unit to the centroid 2302. That is, 7.3% of the 2D confidence region 2306 overlaps with the second building polygon 2310.
• the third building polygon 2312 corresponds to a building located at “345 Main Street” that is 20 m tall, has 6 stories, has a 42.8% overlap region 2322 with the 2D confidence region 2306, and has a nearest distance of 0 units to the centroid 2302, since the centroid is located within 2312. That is, 42.8% of the 2D confidence region 2306 overlaps with the third building polygon 2312.
• an estimated user position e.g., located at the centroid 2302
• an estimated user altitude are determined (i.e., a 3D (three-dimensional) estimated position).
• the estimated user position and estimated altitude may be determined using a mobile device (i.e., that the user is carrying) and may refer to an estimated position and/or estimated altitude of a mobile device.
• the estimated user position and estimated altitude may be values retrieved from a server or another data source.
• a 2D position of a mobile device may be determined using positioning signals received at the mobile device.
• An altitude of the mobile device may be determined using similar positioning signals and/or may be based on atmospheric pressure measurements made using a barometric pressure sensor of the mobile device.
• one or more physical buildings that correspond to the estimated user position are identified.
• an estimated 3D fix e.g., a cylindrical volume that includes all 3D uncertainties, or an ellipsoid, etc.
• all building polygons that overlap with the 2D confidence region of the estimated position e.g., 2306 are included within a set of potential buildings in which the user device could be located.
• the 2D confidence region 2306 overlaps with building polygons 2308, 2310, and 2312.
• the initial set of potential buildings includes buildings corresponding to the building polygons 2308, 2310, and 2312.
• potential buildings may be removed from the set if a height of those buildings does not overlap in altitude with the estimated altitude of the estimated position. For example, if the estimated altitude of the user device is 100 m, then any building that has a height of less than 100 m (or less than 100 m and some buffer to account for rounding, altitude uncertainty, and building database uncertainty) would be removed from the set of potential buildings (e.g., if a user is estimated to be near the top floor of the Empire State Building and has a 400 m 2D uncertainty, the user is not likely in the other buildings and thus a much better 2D uncertainty may be inferred than what is provided).
• a height of those buildings does not overlap in altitude with the estimated altitude of the estimated position. For example, if the estimated altitude of the user device is 100 m, then any building that has a height of less than 100 m (or less than 100 m and some buffer to account for rounding, altitude uncertainty, and building database uncertainty) would be removed from the set of potential buildings (e.
• the remaining number of buildings in the set of potential buildings is equal to zero, there are several options that include any combination of: not returning an estimated floor number to a user, warning the user that no corresponding building is detected in the area of the estimated position, and/or, using an estimated floor number “base case”.
• the estimated floor number base case assumes no constraints on building height or the number of stories and translates the height-above-ellipsoid or height-above-terrain associated with the estimated position to an estimated floor number and an estimated floor number confidence using the process 2200, but warns the user that no building is detected.
• the height-above-ellipsoid or height-above- terrain associated with the estimated position is translated to an estimated floor number and an estimated floor number confidence using the process 2200.
• the height-above-ellipsoid or height-above-terrain associated with the estimated position is translated to an estimated floor number, and an estimated floor number confidence using the process 2200.
• an estimated floor number for each building is returned to the user, listed separately, but ordered by likely building.
• the most likely building may be estimated by computing a metric of the distance between the centroid (e.g., 2302) and each building polygon and sorting by that metric.
• the metric is a mean distance, a median distance, or an overlap of a 2D confidence region (e.g., 2306) and the building polygons.
• the potential buildings may be sorted by percent overlap with the 2D confidence region (e.g., 2306).
• the metric is a measure of overlap area, and the buildings may be sorted by the area of an overlapped building polygon with a user’s 2D confidence region rather than by percentage.
• the metric is a proportional overlap and the buildings may be sorted by the proportional overlap of an overlapped building polygon with a user’s 2D confidence region.
• a proportional overlap is calculated by dividing an overlap area by the total area of the building polygon. As such, a very small building polygon that is completely overlapped with a user’s 2D confidence region would be sorted ahead of a very large building that is partially overlapped with a user’s 2D confidence region.
• an absolute aggregate altitude envelope distribution that corresponds to each of the potential buildings in the set is identified.
• the absolute aggregate altitude envelope distributions are retrieved from the server or database that was used to store the absolute aggregate altitude envelope distribution as described with reference to step 1412 of the process 1400.
• a list of estimated floor numbers is determined using the estimated altitude and the absolute aggregate altitude envelope distribution for that building.
• an estimated floor label is determined using the estimated floor number to estimated floor label mapping described with reference to FIG. 21.
• the estimated floor number may be reported, or returned, to an endpoint (e.g., a user, a mobile device, a server, or a device that initiated the process 2200).
• an endpoint e.g., a user, a mobile device, a server, or a device that initiated the process 2200.
• the estimated floor number is returned to the endpoint via an application programming interface (API).
• API application programming interface
• Estimated floor number ⁇ ADDRESS0, FLOORRANGEO, STATUS0 ⁇ , ⁇ ADDRESS 1, FLOORRANGE1, STATUS1 ⁇
• the floor or address representation can be ranked by percent confidences, but not reveal the individual confidences, e.g.,
• the floor representation can be the highest confidence floor / most likely floor (with or without confidences revealed), followed by a range of floors (with or without confidences revealed), e.g., Estimated
• the address representation can be defined with percent confidences as well as absolute confidence values, e.g., [0149]
• additional information is available about unpopulated buildings, they may be removed from the API response, or the user may be warned. For example, if 234 Main Street were an abandoned building, e.g.,
• floor numbers that are restricted or off-limits e.g., an unattended server room
• the floor representation and the building representation can be defined with percent confidences, but only the building having the highest confidence value and the floor having the highest confidence value are returned,
• each geographical region may have hundreds, or even thousands, of physical buildings, and each building may have many possible permutations of floor numbers and floor labels, and because large datasets of regional and cultural rules are considered, in addition to the consideration of large datasets which may contain known apartment numbers, elevator button information, etc.
• the processes disclosed herein are advantageously performed by one or more mobile devices and/or servers and are not performed manually. This is because such mobile devices are operable to measure physical atmospheric effects and to transmit data representative of those measurements to one or more servers that are operable to access and operate on large datasets.
• selection of altitude envelope distribution constraints, validation of altitude envelope distribution constraints, construction of a range of altitude envelope distributions, application of altitude envelope distribution constraints to the altitude envelope distributions, generation of resultant aggregate altitude envelope distributions, and generation of an absolute aggregate altitude envelope distribution may be repeated hundreds, if not thousands of times for a region. Additionally, there may be hundreds, if not thousands of regions considered. Because the processes disclosed herein are advantageously performed by mobile devices and/or servers, datasets that provide mappings of an estimated altitude to an estimated floor number and/or floor label may advantageously be inexpensively and quickly created for any number of regions as compared to manual processes that involve surveying buildings and/or manually retrieving and manually creating such mappings.
• aggregate floor distributions may be selectively chosen per floor number if so desired in order to tighten the bounds on individual floor distributions.
• the floor-to-floor separation, as well as the floor-to-ceiling separation, and the boundary thickness do need to be uniform throughout a building.
• subterranean floors i.e., basement levels
• building depths analogous to building heights
• the number of basement floors may not be well documented nor easy to assess.
• some assumptions about ventilation and building foundation may be made to restrict the number of below-ground stories and/or building depths.
• assumptions may be directly made about the number of below-ground levels/stories and/or depths. For example, one assumption may be that a building may have no more than five below-ground levels/stories, may be no more than 20 m deep, or have no more than five below-ground levels/stories that sum to more than 20 m of depth. Other assumptions concerning building depth and below-ground levels/stories may be made and may be based on the geographical region in which the building is located.
• building floors can reasonably be assumed to be level (or flat) whereas terrain may not necessarily be level, in some embodiments it is preferred to convert from a mobile device’s height-above-ellipsoid altitude value to an estimated floor number, described below, directly using the building’s absolute aggregate altitude envelope distribution instead of from a mobile device’s height-above-terrain.
• a mobile device for example, in a building erected on sloped terrain with a portion of the lower levels underground on one side of the building, as a user walks horizontally around the building’s floor without changing floors, the height-above-ellipsoid value is expected to not change very much.
• the mobile device s height-above-terrain value may change if the underlying terrain database indicates sloped terrain (that has since been excavated out for the building to be erected). Therefore, height-above-terrain is potentially less stable than height-above-ellipsoid and could inadvertently induce errors in estimated floor number reporting.
• the estimated altitude data of a mobile device can be measured in many ways, as mentioned above, such as Height Above Ellipsoid (HAE), Mean Sea- Level (MSL), Height Above Terrain (HAT), etc.
• HAT Height Above Ellipsoid
• MSL Mean Sea- Level
• HAT Height Above Terrain
• the building database includes data that is measured/represented in height relative to the ground (i.e., HAT), meaning the building database provided aggregate altitude envelope distributions for different floors/floor numbers, then the estimated altitude data of a mobile device would need to be converted to HAT if necessary, by processes known in the art. Additionally, if the building database includes data that is measured/represented in absolute height (i.e.
• HAE or MSL meaning the building database provided absolute aggregate altitude envelope distributions for different floors/floor numbers, then the estimated altitude data of a mobile device would need to be converted to HAE or MSL if necessary, by processes known in the art.
• Any method described or otherwise enabled by the disclosure herein may be implemented by hardware components (e.g., machines), software modules (e.g., stored in machine- readable media), or a combination thereof.
• any method described or otherwise enabled by the disclosure herein may be implemented by any concrete and tangible system described herein.
• machines may include one or more computing device(s), processor(s), controller(s), integrated circuit(s), chip(s), system(s) on a chip, server(s), programmable logic device(s), field-programmable gate array(s), electronic device(s), special-purpose circuitry, and/or other suitable device(s) described herein or otherwise known in the art.
• machine-readable media includes all forms of machine-readable media, including but not limited to one or more non-volatile or volatile storage media, removable or non-removable media, integrated circuit media, magnetic storage media, optical storage media, or any other storage media, including RAM, ROM, and EEPROM, that may be patented under the laws of the jurisdiction in which this application is filed, but does not include machine-readable media that cannot be patented under the laws of the jurisdiction in which this application is filed (e.g., transitory propagating signals).
• Methods disclosed herein provide sets of rules that are performed.
• Systems that include one or more machines and one or more non- transitory machine-readable media for implementing any method described herein are also contemplated herein.
• One or more machines that perform or implement, or are configured, operable, or adapted to perform or implement operations comprising the steps of any methods described herein are also contemplated herein.
• Each method described herein that is not prior art represents a specific set of rules in a process flow that provides significant advantages in the field of characterizing height-above-terrain confidence.
• Method steps described herein may be order independent and can be performed in parallel or in an order different from that described if possible to do so. Different method steps described herein can be combined to form any number of methods, as would be understood by one of ordinary skill in the art.
• any known communication pathways and protocols may be used to transmit information (e.g., data, commands, signals, bits, symbols, chips, and the like) disclosed herein unless otherwise stated.
• the words comprise, comprising, include, including and the like are to be construed in an inclusive sense (i.e., not limited to) as opposed to an exclusive sense (i.e., consisting only of). Words using the singular or plural number also include the plural or singular number, respectively, unless otherwise stated.
• the word “or” and the word “and” as used in the Detailed Description cover any of the items and all of the items in a list unless otherwise stated. The words some, any, and at least one refer to one or more.
• access to data from a source of data may be achieved using known techniques (e.g., requesting component requests the data from the source via a query or other known approach, the source searches for and locates the data, and the source collects and transmits the data to the requesting component, or other known techniques).
• FIG. 24 illustrates components of a transmitter 2401, a mobile device 2402, and a server 2403, in accordance with some embodiments. Examples of communication pathways are shown by arrows between components.
• each of the transmitters 2401 may include: a mobile device interface 11 for exchanging information with a mobile device (e.g., antenna(s) and RF front-end components known in the art or otherwise disclosed herein); one or more processor(s) 12; memory/data source 13 for providing storage and retrieval of information and/or program instructions; atmospheric sensor(s) 14 for measuring environmental conditions (e.g., pressure, temperature, humidity, other) at or near the transmitter; a server interface 15 for exchanging information with a server (e.g., an antenna, a network interface, or other); and any other components known to one of ordinary skill in the art.
• a mobile device interface 11 for exchanging information with a mobile device (e.g., antenna(s) and RF front-end components known in the art or otherwise disclosed herein); one or more processor(s) 12; memory/data source 13 for providing storage and retrieval of information and/or program instructions; atmospheric sensor(s) 14 for measuring environmental conditions (e.g., pressure, temperature, humidity, other) at or near the
• the memory/data source 13 may include memory storing software modules with executable instructions, and the processor(s) 12 may perform different actions by executing the instructions from the modules, including: (i) performance of part or all of the methods as described herein or otherwise understood by one of skill in the art as being performable at the transmitter; (ii) generation of positioning signals for transmission using a selected time, frequency, code, and/or phase; (iii) processing of signaling received from the mobile device or other source; or (iv) other processing as required by operations described in this disclosure.
• Signals generated and transmitted by a transmitter may carry different information that, once determined by a mobile device or a server, may identify the following: the transmitter; the transmitter’s position; environmental conditions at or near the transmitter; and/or other information known in the art.
• the mobile device 2402 may include: a transmitter interface 21 for exchanging information with a transmitter (e.g., an antenna and RF front end components known in the art or otherwise disclosed herein); one or more processor(s) 22; memory/data source 23 for providing storage and retrieval of information and/or program instructions; atmospheric sensor(s) 24 (such as barometers and temperature sensors) for measuring environmental conditions (e.g., pressure, temperature, other) at the mobile device; other sensor(s) 25 for measuring other conditions (e.g., inertial sensors for measuring movement and orientation); a user interface 26 (e.g., display, keyboard, microphone, speaker, other) for permitting a user to provide inputs and receive outputs; another interface 27 for exchanging information with the server or other devices external to the mobile device (e.g., a transmitter interface 21 for exchanging information with a transmitter (e.g., an antenna and RF front end components known in the art or otherwise disclosed herein); one or more processor(s) 22; memory/data source 23 for providing storage and retrieval of information
• a GNSS interface and processing unit (not shown) are contemplated, which may be integrated with other components (e.g., the interface 21 and the processors 22) or a standalone antenna, RF front end, and processors dedicated to receiving and processing GNSS signaling.
• the memory/data source 23 may include memory storing software modules with executable instructions, and the processor(s) 22 may perform different actions by executing the instructions from the modules, including: (i) performance of part or all of the methods as described herein or otherwise understood by one of ordinary skill in the art as being performable at the mobile device; (ii) estimation of an altitude of the mobile device based on measurements of pressure from the mobile device and transmitted s), temperature measurement(s) from the transmitter(s) or another source, and any other information needed for the computation); (iii) processing of received signals to determine position information (e.g., times of arrival or travel time of the signals, pseudoranges between the mobile device and transmitters, transmitter atmospheric conditions, transmitter and/or locations or other transmitter information); (iv) use of position information to compute an estimated position of the mobile device; (v) determination of movement based on measurements from inertial sensors of the mobile device; (vi) GNSS signal processing; or (vii) other processing as required by operations described in this disclosure.
• position information e.g., times
• the server 2403 may include: a mobile device interface 31 for exchanging information with a mobile device (e.g., an antenna, a network interface, or other); one or more processor(s) 32; memory/data source 33 for providing storage and retrieval of information and/or program instructions; a transmitter interface 34 for exchanging information with a transmitter (e.g., an antenna, a network interface, or other); and any other components known to one of ordinary skill in the art.
• a mobile device interface 31 for exchanging information with a mobile device (e.g., an antenna, a network interface, or other); one or more processor(s) 32; memory/data source 33 for providing storage and retrieval of information and/or program instructions; a transmitter interface 34 for exchanging information with a transmitter (e.g., an antenna, a network interface, or other); and any other components known to one of ordinary skill in the art.
• the memory/data source 33 may include memory storing software modules with executable instructions, and the processor(s) 32 may perform different actions by executing instructions from the modules, including: (i) performance of part or all of the methods as described herein or otherwise understood by one of ordinary skill in the art as being performable at the server; (ii) estimation of an altitude of the mobile device; (iii) computation of an estimated position of the mobile device; or (iv) other processing as required by operations described in this disclosure. Steps performed by servers as described herein may also be performed on other machines that are remote from a mobile device, including computers of enterprises or any other suitable machine.
• Certain aspects disclosed herein relate to estimating the positions of mobile devices — e.g., where the position is represented in terms of: latitude, longitude, and/or altitude coordinates; x, y, and/or z coordinates; angular coordinates; or other representations.
• Various techniques to estimate the position of a mobile device can be used, including trilateration, which is the process of using geometry to estimate the position of a mobile device using distances traveled by different “positioning” (or “ranging”) signals that are received by the mobile device from different beacons (e.g., terrestrial transmitters and/or satellites).
• Positioning systems and methods that estimate a position of a mobile device (in terms of latitude, longitude and/or altitude) based on positioning signals from beacons (e.g., transmitters, and/or satellites) and/or atmospheric measurements are described in co-assigned U.S. Pat. No. 8,130,141, issued March 6, 2012, and U.S. Pat. No.
• positioning system may refer to satellite systems (e.g., Global Navigation Satellite Systems (GNSS) like GPS, GLONASS, Galileo, and Compass/Beidou), terrestrial transmitter systems, and hybrid satellite/terrestrial systems.
• GNSS Global Navigation Satellite Systems

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