CN110554355A - Target positioning system and method - Google Patents
Target positioning system and method Download PDFInfo
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- CN110554355A CN110554355A CN201910707925.2A CN201910707925A CN110554355A CN 110554355 A CN110554355 A CN 110554355A CN 201910707925 A CN201910707925 A CN 201910707925A CN 110554355 A CN110554355 A CN 110554355A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/16—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using electromagnetic waves other than radio waves
Abstract
The embodiment of the invention discloses a target positioning system and a method, wherein the system comprises: a plurality of infrared sensor nodes and a positioning device; each infrared sensor node comprises a plurality of infrared sensors and a processor connected with the plurality of infrared sensors; the infrared sensor is used for acquiring infrared signals; the processor is used for determining range information of a target according to infrared signals collected by a plurality of infrared sensors connected with the processor, and sending the determined range information to the positioning equipment; and the positioning equipment is used for carrying out fusion processing on the range information sent by the processor of each infrared sensor node by using a data fusion algorithm to obtain the position of the target. Therefore, in the scheme, the target is positioned according to the infrared signals, the infrared signals are less influenced by the ambient light, and the positioning accuracy is improved.
Description
Technical Field
The present invention relates to the field of positioning technologies, and in particular, to a target positioning system and method.
Background
In some scenarios, it is often necessary to locate objects such as people and vehicles. Existing positioning solutions typically include: and identifying a target to be positioned in the image acquired by the camera, and positioning the target according to the time and the position of the target acquired by the camera.
However, the positioning scheme is greatly influenced by ambient light, for example, under the conditions of weak light such as night, rainy days and the like, the definition of an image acquired by a camera is poor, and the positioning accuracy is low.
Disclosure of Invention
In view of the above, the present invention provides a target positioning system and method to improve the positioning accuracy.
Based on the above object, an embodiment of the present invention provides a target positioning system, including: a plurality of infrared sensor nodes and a positioning device; each infrared sensor node comprises a plurality of infrared sensors and a processor connected with the plurality of infrared sensors;
the infrared sensor is used for acquiring infrared signals;
The processor is used for determining range information of a target according to infrared signals collected by a plurality of infrared sensors connected with the processor, and sending the determined range information to the positioning equipment;
And the positioning equipment is used for carrying out fusion processing on the range information sent by the processor of each infrared sensor node by using a data fusion algorithm to obtain the position of the target.
optionally, the processor is specifically configured to:
aiming at each infrared sensor connected with the infrared sensor, acquiring an infrared signal acquired by the infrared sensor and acquiring incremental data corresponding to the infrared signal; generating an event signal corresponding to the infrared sensor based on the infrared signal and the incremental data, wherein the event signal is a signal indicating whether a target is detected or not;
And determining range information of the target according to the generated event signal corresponding to each infrared sensor, and sending the determined range information to the positioning equipment.
Optionally, each infrared sensor node includes N infrared sensors uniformly arranged in the circumferential direction, N is a positive integer greater than 1, the N infrared sensors form 2N detection regions, the 2N detection regions include N overlapping regions and N non-overlapping regions, the overlapping regions are regions where the acquisition ranges of adjacent infrared sensors overlap, and the non-overlapping regions are regions where the acquisition ranges of adjacent infrared sensors do not overlap;
The processor is further configured to: and determining the detection area information of the target according to the generated event signal corresponding to each infrared sensor, and sending the determined detection area information to the positioning equipment.
Optionally, the processor is further configured to:
if a plurality of candidate detection areas are determined according to the generated event signal corresponding to each infrared sensor, determining the probability of the target existing in each candidate detection area;
and determining the detection region information of the target based on the probability corresponding to each candidate detection region.
optionally, the information of the detection area where the target is located is: information of an angular bisector of a detection area where the target is located; the plurality of infrared sensor nodes comprise a central node and a plurality of peripheral nodes; the positioning device is further configured to:
Determining an intersection point of the angular bisector corresponding to the central node and the angular bisector corresponding to the peripheral node as a first intersection point according to angular bisector information sent by a processor of each infrared sensor node; determining an intersection point of the angle bisectors corresponding to the plurality of peripheral nodes as a second intersection point;
Clustering the first intersection point to obtain a first clustering result;
Clustering the second intersection points based on the first clustering result to obtain a second clustering result, and determining one or more targets according to the second clustering result;
for each target, a center point of an intersection of the bisectors associated with the target is determined, and a location of the target is determined based on the center point.
Optionally, the positioning device is specifically configured to:
for each target, determining a central point of an intersection point of angle bisectors associated with the target, and determining the central point as the position of the target;
Alternatively, the first and second electrodes may be,
for each target, determining a center point of an intersection point of the angle bisectors associated with the target;
And eliminating angular bisector intersection points of which the distance between the angular bisector intersection points and the central point is greater than a preset threshold value from the angular bisector intersection points associated with the target, and returning to the step of determining the central point of the angular bisector intersection points associated with the target until the central point is determined as the position of the target under the condition that the distance between each angular bisector intersection point and the central point is less than or equal to the preset threshold value.
Optionally, each infrared sensor node includes 6 infrared sensors, the 6 infrared sensors are arranged in a circumferential shape, the plurality of peripheral nodes are 8 infrared sensor nodes arranged in a rectangular shape, and the central node is located in the center of the rectangular shape.
Based on the above object, an embodiment of the present invention further provides a target positioning method, which is applied to a positioning device in a target positioning system, where the system includes a plurality of infrared sensor nodes and a positioning device; each infrared sensor node comprises a plurality of infrared sensors and a processor connected with the plurality of infrared sensors; the method comprises the following steps:
Receiving range information of a target sent by a processor of each infrared sensor node; the range information is determined by the processor according to infrared signals collected by a plurality of infrared sensors connected with the processor;
and performing fusion processing on the received range information by using a data fusion algorithm to obtain the position of the target.
optionally, the plurality of infrared sensor nodes include a central node and a plurality of peripheral nodes; each infrared sensor node forms a plurality of detection areas; the range information is angular bisector information of the detection area;
The using a data fusion algorithm to perform fusion processing on the received range information to obtain the position of the target includes:
determining an intersection point of the angular bisector corresponding to the central node and the angular bisector corresponding to the peripheral node as a first intersection point according to angular bisector information sent by a processor of each infrared sensor node; determining an intersection point of the angle bisectors corresponding to the plurality of peripheral nodes as a second intersection point;
clustering the first intersection point to obtain a first clustering result;
Clustering the second intersection points based on the first clustering result to obtain a second clustering result, and determining one or more targets according to the second clustering result;
For each target, a center point of an intersection of the bisectors associated with the target is determined, and a location of the target is determined based on the center point.
Optionally, the determining, for each object, a central point of an intersection of angle bisectors associated with the object, and determining a position of the object based on the central point includes:
For each target, determining a central point of an intersection point of angle bisectors associated with the target, and determining the central point as the position of the target;
Alternatively, the first and second electrodes may be,
For each target, determining a center point of an intersection point of the angle bisectors associated with the target;
and eliminating angular bisector intersection points of which the distance between the angular bisector intersection points and the central point is greater than a preset threshold value from the angular bisector intersection points associated with the target, and returning to the step of determining the central point of the angular bisector intersection points associated with the target until the central point is determined as the position of the target under the condition that the distance between each angular bisector intersection point and the central point is less than or equal to the preset threshold value.
With the illustrated embodiment of the present invention applied, a target positioning system includes: a plurality of infrared sensor nodes and a positioning device; each infrared sensor node comprises a plurality of infrared sensors and a processor connected with the plurality of infrared sensors; the infrared sensor is used for acquiring infrared signals; the processor is used for determining range information of a target according to infrared signals collected by a plurality of infrared sensors connected with the processor, and sending the determined range information to the positioning equipment; and the positioning equipment is used for carrying out fusion processing on the range information sent by the processor of each infrared sensor node by using a data fusion algorithm to obtain the position of the target. Therefore, in the scheme, the target is positioned according to the infrared signals, the infrared signals are less influenced by the ambient light, and the positioning accuracy is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
fig. 1 is a schematic structural diagram of a target positioning system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an event signal generation according to an embodiment of the present invention;
Fig. 3 is a schematic diagram of a detection area of an infrared sensor according to an embodiment of the present invention;
Fig. 4 is a schematic layout diagram of infrared sensor nodes according to an embodiment of the present invention;
FIGS. 5(a) - (d) are schematic diagrams of target distributions provided by embodiments of the present invention;
FIG. 6 is a schematic diagram of another target distribution provided by an embodiment of the present invention;
FIG. 7 is a schematic diagram illustrating a determination of a target direction according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of another target distribution provided by an embodiment of the present invention;
FIG. 9 is a schematic diagram of another method for determining a target direction according to an embodiment of the present invention;
FIG. 10 is a schematic diagram of another target locating system according to an embodiment of the present invention;
FIG. 11 is a schematic diagram of a target location provided by an embodiment of the present invention;
fig. 12 is a flowchart illustrating a target positioning method according to an embodiment of the present invention.
Detailed Description
in order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to specific embodiments and the accompanying drawings.
it should be noted that all expressions using "first" and "second" in the embodiments of the present invention are used for distinguishing two entities with the same name but different names or different parameters, and it should be noted that "first" and "second" are merely for convenience of description and should not be construed as limitations of the embodiments of the present invention, and they are not described in any more detail in the following embodiments.
In order to solve the above technical problem, an embodiment of the present invention provides a target positioning system and a method thereof, and first, the target positioning system provided by the embodiment of the present invention is described below.
Fig. 1 is a schematic structural diagram of a target positioning system according to an embodiment of the present invention, including:
A plurality of infrared sensor nodes (infrared sensor node 1 … … infrared sensor node M, M being a positive integer greater than 1) 100 and a positioning device 200; each infrared sensor node 100 includes a plurality of infrared sensors (infrared sensor 1 … …, infrared sensor N, N being a positive integer greater than 1) 110 and a processor 120 connected to the plurality of infrared sensors;
An infrared sensor 110 for collecting an infrared signal;
The processor 120 is configured to determine range information of a target according to infrared signals acquired by a plurality of infrared sensors connected to the processor, and send the determined range information to the positioning device;
And the positioning device 200 is configured to perform fusion processing on the range information sent by the processor of each infrared sensor node by using a data fusion algorithm to obtain the position of the target.
For example, the infrared sensor 110 may be a pyroelectric infrared sensor, or may also be another type of infrared sensor, which is not limited in particular.
in one embodiment, the processor 120 may acquire, for each infrared sensor 110 connected to itself, an infrared signal acquired by the infrared sensor, and acquire incremental data corresponding to the infrared signal; generating an event signal corresponding to the infrared sensor based on the infrared signal and the incremental data, wherein the event signal is a signal indicating whether a target is detected or not; and determining range information of the target according to the generated event signal corresponding to each infrared sensor, and sending the determined range information to the positioning equipment.
the present embodiment is explained with reference to fig. 2: fig. 2(a) shows raw data, and the infrared signal may be understood as the collected raw data, and the raw data may be transformed first. The theoretical stable value can be 1024, the difference between the original data and 1024 is calculated, namely data is | data-1024|, the data on the right side of the equation is the original data, and the data on the left side of the equation is the transformed original data.
in one case, the difference between the data at the current time and the data at the previous time may be used as incremental data, i.e., data (i) -data (i-1), data (i) on the right side of the equation indicates the data at the current time, data (i-1) on the right side of the equation indicates the data at the previous time, and data (i) on the left side of the equation indicates the incremental data. The incremental data is transformed, for example, by multiplying the incremental data by k times, i.e., data (i) k × data (i) -data (i-1) |, and data (i) on the left of the equation is the transformed incremental data. Fig. 2(b) shows the transformed raw data and the transformed delta data.
As shown in fig. 2(c), the transformed original data and the transformed incremental data may be combined, for example, the larger value of the transformed original data and the transformed incremental data may be taken as the characteristic value.
as shown in fig. 2(d), the eigenvalue signal in fig. 2(c) may be digitized to obtain a digital signal by setting a fixed threshold. For example, if the feature value is greater than the threshold value, the digital signal is 1, and if the feature value is not greater than the threshold value, the digital signal is 0.
As shown in fig. 2(e), the digital signal obtained in fig. 2(d) may be smoothed into an event signal. The smoothing method may be: when the signal at a certain moment is the same as the signal at the previous moment, no processing is carried out; and when the number of the 1 in the window is larger than half of the window length, the time signal is 1, and otherwise, the time signal is 0.
In the present embodiment, the processor 120 transmits the processed event signal to the processing device 200.
in one embodiment, each infrared sensor node comprises N infrared sensors uniformly arranged in the circumferential direction, the N infrared sensors form 2N detection regions, each of the 2N detection regions comprises N overlapping regions and N non-overlapping regions, the overlapping regions are regions where the acquisition ranges of adjacent infrared sensors overlap, and the non-overlapping regions are regions where the acquisition ranges of adjacent infrared sensors do not overlap.
for example, N may be 6, that is, each infrared sensor node may include 6 infrared sensors, and in one case, the 6 infrared sensors may be arranged in a circumferential shape. As shown in fig. 3, the acquisition range of the 6 infrared sensors is divided into 12 detection regions, wherein (c) - (c) in fig. 3 represent the numbers of the infrared sensors, and (a) - (L) represent the numbers of the detection regions. In fig. 3, the acquisition ranges of adjacent infrared sensors intersect with each other, and the intersecting range is called an overlap region, for example, A, C, E, G, I, K, which are 6 detection regions are overlap regions, B, D, F, H, J, L, which are non-overlap regions.
In this embodiment, the processor 120 may determine, according to the generated event signal corresponding to each infrared sensor, detection area information where the target is located, and send the determined detection area information to the positioning device.
in one embodiment, the detection region information may be a number of the detection region. Taking fig. 3 as an example, if there is only one target, the correspondence relationship between the area where the target is located and the corresponding event signal output by each infrared sensor can be shown in table 1:
TABLE 1
still referring to fig. 3, if the object is located in the a region, the infrared sensors numbered 1 and 6 can detect the object, the infrared sensors numbered 1 and 6 correspond to the event signal of 1, and the other infrared sensors correspond to the event signal of 0. Similarly, if the target is located in the B region, the infrared sensor numbered 1 can detect the target, the infrared sensor numbered 1 corresponds to an event signal of 1, and the other infrared sensors correspond to event signals of 0. Other regions are similar and will not be described one by one.
If only one target is present, the processor 200 may determine the number of detection zones in which the target is located based on table 1 and the event signals corresponding to each infrared sensor associated with itself.
Fig. 3 is an illustration only, and the number and arrangement of the infrared sensors in each infrared sensor node are not limited.
In one case, M may be 9, that is, the system may include 9 infrared sensor nodes, as shown in fig. 4, the 9 infrared sensor nodes may be uniformly arranged in 3 rows and 3 columns, or 8 infrared sensor nodes are uniformly arranged in a rectangle, and the other 1 infrared sensor node is located in the center of the rectangle. Fig. 4 is merely an example, and the number and the arrangement shape of the infrared sensor nodes are not limited, for example, the 8 infrared sensor nodes may be uniformly arranged in a circumferential shape.
continuing with the above example, the detection area information may be the number of the detection area, the processor of each infrared sensor node sends the determined number of the detection area to the positioning apparatus 200, and the positioning apparatus 200 determines the specific location of the target by using a data fusion algorithm based on the numbers of the detection areas.
or, in another embodiment, the detection region information may be angular bisector information of the detection region, so that the processor of each infrared sensor node sends the determined angular bisector information of the detection region where the target is located to the positioning device 200, the positioning device 200 determines a plurality of angular bisector intersection points based on the angular bisector information, and fuses the angular bisector intersection points by using a data fusion algorithm to obtain the specific position of the target.
the length of the angular bisector of each detection area is the distance of the corresponding acquisition range of the infrared sensor, as shown in fig. 3, 12 angular lines with long and short intervals are shared in a 360-degree area, the long angular line is 10m long, the short angular line is 7.5m long, and the large angle error is about 15 °.
in one embodiment, if the processor 120 determines a plurality of candidate detection regions according to the generated event signal corresponding to each infrared sensor, the processor 120 determines a probability that an object exists in each candidate detection region; and determining the detection region information of the target based on the probability corresponding to each candidate detection region.
for example, if the event signal output by each infrared sensor is "111100", it indicates that the two targets are located in the C region and the G region, respectively, as shown in fig. 5 (a); as shown in fig. 5(b), if the event signal output from each infrared sensor is "101101", it indicates that the two targets are located in the a zone and the G zone, respectively. As shown in fig. 5(c), if the event signal output from each infrared sensor is "100110", it indicates that the two targets are located in the B zone and the I zone, respectively. As shown in fig. 5(D), if the event signal "010001" output from each infrared sensor indicates that the two targets are located in the D region and the L region, respectively.
If there are two adjacent "1" s in the event signal output by each infrared sensor, there may be multiple possible target distribution scenarios. For example, referring to fig. 6, if the event signal output by each infrared sensor is "001100", there are 4 possible target distribution cases: there may be one target located in region G and there may be two targets located in regions F and H, or in regions F and G, or in regions G and H, respectively. For convenience of description, these detection regions in which the target may exist are referred to as candidate detection regions.
In the above one embodiment, the detection region information is angular bisector information of the detection region, and the positioning device determines intersection points of a plurality of angular bisectors based on the angular bisector information; still referring to fig. 6, if the intersection points of the bisectors of all candidate probe regions in fig. 6 are determined, more false points occur, which brings great difficulty to subsequent data fusion and introduces great errors. This embodiment can solve this problem by introducing a probability point of view.
Assuming that there are two targets, as can be seen from FIG. 6, one target is located in region G or region H and the other target is located in region F or region G; if one target is located in zone G, another target can also be located in zone F or zone H; if one target is located in zone H, another target may be located in zone G or zone F; if one target is located in zone F, another target may be located in zone G or zone H. From the perspective of probability, the probability that the target is located in the F region, the G region or the H region is equal. In this case, as shown in fig. 7, angular bisectors of the G area and the F area may be determined, and are recorded as "angular line 1", where the angular line 1 is an angular bisector of a detection area where a target is located; determining a bisector of the angle lines of the G region and the H region, and marking the bisector as an angle line 2, wherein the angle line 2 is an angle bisector of a detection region where another target is located; the length of the angle line is also the average of the two angle lines.
as another example, referring to fig. 8, if the event signal output by each infrared sensor is "111000", there are 3 possible target distribution cases: there may be two targets located in zones B and E, or in zones F and C, or in zones E and C, respectively. For convenience of description, these detection regions in which the target may exist are referred to as candidate detection regions.
As can be seen from FIG. 8, one target is located in zone B or zone C and the other target is located in zone F or zone E. For targets located in zone B or zone C: if it is located in zone B, another target is located in zone E; if it is located in zone C, another target may be located in zone E or zone F. Therefore, the probability of the target being located in region E is 2/3, and the probability of being located in region F is 1/3. As shown in fig. 9, a line closer to the E area in the trisecting lines of the angle lines of the E area and the F area is determined and is marked as "angle line 1", and the angle line 1 is an angle bisector of a detection area where a target is located.
similarly, for targets located in region F or E: if it is located in zone F, another target is located in zone C; if it is located in zone E, another target may be located in zone B or zone C. Therefore, the probability of the target being located in the region C is 2/3, and the probability of being located in the region B is 1/3. As shown in fig. 9, a line closer to the C area in the trisecting lines of the angle lines of the B area and the C area is determined and is marked as "angle line 2", and the angle line 2 is an angle bisector of a detection area where another target is located.
As can be seen, in the present embodiment, if there are a plurality of target distributions, the diagonals are fused based on the probability corresponding to each candidate detection region. Therefore, for subsequent data fusion, the data classification is clearer, the complexity of data processing is reduced, and certain precision can be ensured.
as described above, the positioning device 200 determines a plurality of angle bisector intersection points, and fuses the angle bisector intersection points by using a data fusion algorithm to obtain a specific target position. Taking an object as an example, the pointing device 200 may determine the location of the object based on the midpoint of the intersection of these bisectors. For example, in one embodiment, a center value method may be used, and the locating device 200 may determine the midpoint of the intersection of the bisectors as the location of the target.
For another example, in another embodiment, a loop elimination method may be adopted, and the positioning apparatus 200 may determine a midpoint of the intersection points of the angle bisectors, then eliminate the intersection points of the angle bisectors whose distance from the central point is greater than a preset threshold, and return to the step of determining the midpoint of the intersection points of the angle bisectors, until the central point is determined as the position of the target when the distance between each intersection point of the angle bisectors and the central point is less than or equal to the preset threshold. In the embodiment, the edge points are repeatedly eliminated, the central point is repeatedly determined, and the positioning accuracy is improved.
in the above embodiment, as shown in fig. 4, 8 infrared sensor nodes are uniformly arranged in a rectangle, and the other 1 infrared sensor node is located in the center of the rectangle. For convenience of description, the infrared sensor node located at the center of the rectangle is referred to as a center node, and the other infrared sensor nodes are referred to as peripheral nodes.
In one embodiment, the positioning apparatus 200 may determine, as the first intersection point, an intersection point of the angular bisector corresponding to the central node and the angular bisector corresponding to the peripheral node according to the angular bisector information sent by the processor of each infrared sensor node; determining an intersection point of the angle bisectors corresponding to the plurality of peripheral nodes as a second intersection point; clustering the first intersection point to obtain a first clustering result; clustering the second intersection points based on the first clustering result to obtain a second clustering result, and determining one or more targets according to the second clustering result; for each target, a center point of an intersection of the bisectors associated with the target is determined, and a location of the target is determined based on the center point.
generally, after an object enters the acquisition range of the infrared sensor node, the central node can detect the object. In this embodiment, clustering is performed based on the first intersection point, that is, clustering is performed based on the intersection point of the angular bisector associated with the center node, and then clustering is performed on the intersection points of the other angular bisectors based on the clustering result. Therefore, compared with clustering based on intersection points of all angle bisectors, the method has the advantages of smaller calculated amount and more accurate clustering result.
If a plurality of targets are determined by the clustering result, each target can be positioned respectively. As described above, the positioning apparatus may position the target by using a median method or a cyclic elimination method. If the center value method is adopted, in this embodiment, the positioning apparatus 200 may determine, for each object, a center point of an intersection of bisectors associated with the object, and determine the center point as the position of the object.
if the loop elimination method is adopted, in the embodiment, the positioning apparatus 200 may determine, for each object, a center point of an intersection point of bisectors of angles associated with the object; and eliminating angular bisector intersection points of which the distance between the angular bisector intersection points and the central point is greater than a preset threshold value from the angular bisector intersection points associated with the target, and returning to the step of determining the central point of the angular bisector intersection points associated with the target until the central point is determined as the position of the target under the condition that the distance between each angular bisector intersection point and the central point is less than or equal to the preset threshold value.
By applying the embodiment of the invention, on the first hand, the target is positioned according to the infrared signal, the infrared signal is less influenced by the ambient light, and the positioning accuracy is improved. Secondly, in some related positioning schemes, a target needs to carry a positioning device, for example, a person wears a bracelet, carries a smart phone and other devices that can be used for positioning, or a vehicle needs to be provided with a positioning system; it can be seen that this solution requires the object to be fitted and is not suitable for non-fitted object positioning. In the scheme, the target does not need to carry a positioning device, and the method and the device are suitable for non-matching type target positioning. In the third aspect, the infrared sensor is low in price and low in power consumption, so that the positioning cost is low by using the scheme.
at present, it is generally considered that the available information that can be extracted from the signals collected by the infrared sensor is less, and therefore, the infrared sensor is generally considered to be not suitable for target positioning. In the scheme, the accurate target positioning can be realized by the aid of a reasonable system design and a data processing process of the processor and the positioning equipment.
one specific embodiment is described below:
As shown in fig. 10, the system may include 8 peripheral infrared sensor nodes, 1 central infrared sensor node, 1 sink node and 1 host computer, and the system may adopt a multi-hop Mesh (wireless Mesh network) structure. For example, the 8 peripheral infrared sensor nodes (abbreviated as peripheral nodes in fig. 10), 1 central infrared sensor node (abbreviated as central node in fig. 10), and 1 sink node may communicate with each other based on the ZigBee (ZigBee, a low-speed short-distance transmission wireless internet protocol) Z-Stack protocol. For example, the 9 infrared sensor nodes may be uniformly deployed within an area of 10m × 10 m.
In the system shown in fig. 10, the infrared sensor node collects the infrared signal and performs preliminary signal processing, and the processed effective data is directly or indirectly sent to the sink node. When the infrared sensor node cannot communicate with the sink node due to the communication distance problem, the central infrared sensor node can also serve as a routing node, transmission data of the infrared sensor node is sent to the routing node firstly, and then sent to the sink node by the routing node, and under the condition, the central infrared sensor node simultaneously plays a role in signal acquisition and processing and data transfer. The sink node receives the transmission data of all the infrared sensor nodes, performs some processing operations such as filtering on the received data, and then sends the processed data to the upper computer. The upper computer can be understood as the positioning device in the embodiment, the upper computer performs target positioning based on the received data, in addition, a user can observe monitoring data in real time through observation software of the upper computer, and the user can also store the data.
In this embodiment, a Mesh network structure is adopted, which has the following advantages:
(1) Rapid deployment and easy installation. Due to the simple installation, new infrared sensing nodes can be easily added to expand the coverage area and the network capacity.
(2) non line-of-sight transmission. In the Mesh network, the transmission data can automatically select the optimal path, continuously jump from one node to another node and finally reach the sink node.
(3) the robustness is strong. Mesh networks are more robust than single-hop networks because they do not depend on the performance of a single node. In a single-hop network, if a node fails, the entire network is broken down. In the Mesh network structure, each node has one or more paths for transmitting data. If the nearest node fails or is interfered, the transmission data is automatically routed to the standby path for transmission.
(4) the structure is flexible. In a single-hop network, if several nodes need to transmit data simultaneously, the nodes all transmit data to the sink node, and communication congestion may occur. In the multi-hop network, the nodes can transmit data through other different nodes, and the condition of communication congestion is reduced.
(5) High bandwidth. The physical characteristics of wireless communications dictate that high bandwidth is more readily achieved as the distance over which the communications are transmitted is shorter, as various interference and other factors that cause data loss increase with increasing wireless transmission distance. And by adopting the Mesh network, data can be transmitted through a plurality of short hops, so that higher network bandwidth can be obtained.
Each infrared sensor node includes a plurality of infrared sensors and a processor. Referring to fig. 3, each infrared sensor node may include 6 infrared sensors, and the 6 infrared sensors may be arranged in a circumferential shape. The acquisition range of the 6 infrared sensors is divided into 12 detection areas, wherein (r) - (L) in fig. 3 represent the numbers of the infrared sensors, and (a) - (L) represent the numbers of the detection areas. In fig. 3, the acquisition ranges of adjacent infrared sensors intersect with each other, and the intersecting range is called an overlap region, for example, A, C, E, G, I, K, which are 6 detection regions are overlap regions, B, D, F, H, J, L, which are non-overlap regions.
when the target passes through the acquisition range of one infrared sensor node, 6 complete sinusoidal signals are generated under the ideal condition. Assuming that the target is a person, the normal walking speed of the person is about 2m/s, assuming that the person enters the acquisition range when the distance between the person and the infrared sensor is 0.3m, and the distance of the person passing through the whole acquisition range is the required time isthe signal frequency at this time is about 6/0.2356-25 Hz, so the frequency of the effective signal collected by the infrared sensor is considered to be not higher than 25 Hz. According to Shannon's sampling theorem, the signal acquisition frequency of the infrared sensor is greater than 50 Hz. In addition, the signal acquired by the infrared sensor can be amplified through the signal conditioning circuit.
The processor generates event signals corresponding to each infrared sensor according to the processing flow shown in fig. 2, and determines each candidate detection area in which the target may exist according to the event signals. If a plurality of candidate detection regions are determined, the processor determines the probability of the target existing in each candidate detection region; and determining the angular bisector information of the detection region where the target is located based on the probability corresponding to each candidate detection region.
And the processor of each infrared sensor node sends the determined angular bisector information to the sink node, and the sink node sends the angular bisector information to the upper computer. The upper computer can determine the intersection points of the angle bisectors according to the information of the angle bisectors and cluster the intersection points of the angle bisectors. For example, clustering may be performed based on the intersection points of the angle bisectors associated with the central infrared sensor node, and then clustering may be performed on the intersection points of the other angle bisectors based on the clustering result. Therefore, compared with clustering based on intersection points of all angle bisectors, the method has the advantages of smaller calculated amount and more accurate clustering result.
If a plurality of targets are determined through the clustering result, the upper computer can respectively position each target. The upper computer can position the target by adopting a central value method or a cyclic elimination method. If a central value method is adopted, the upper computer can determine the central point of the intersection point of the angle bisectors associated with each target according to each target, and the central point is determined as the position of the target.
If the cyclic elimination method is adopted, the upper computer can determine the central point of the intersection point of the angular bisector associated with each target; and eliminating angular bisector intersection points of which the distance between the angular bisector intersection points and the central point is greater than a preset threshold value from the angular bisector intersection points associated with the target, and returning to the step of determining the central point of the angular bisector intersection points associated with the target until the central point is determined as the position of the target under the condition that the distance between each angular bisector intersection point and the central point is less than or equal to the preset threshold value.
Referring to fig. 11, numerals 1 to 6 in fig. 11 indicate 6 infrared sensors, a broken straight line in fig. 11 indicates angle bisectors of a detection region where an object is located, and intersection points of all the angle bisectors are obtained, as indicated by hollow dots in fig. 11. These intersections are clustered, and the two elliptical areas in FIG. 11 indicate that two objects are identified by the clustering. The hollow dots outside the elliptical region represent culled false points. For each elliptical region, the hollow dots in the elliptical region are fused to obtain the position of a target, as shown by the solid dots in fig. 11. The triangle in fig. 11 can be understood as the actual position of the target, and it can be seen that the error between the target position determined by the present solution and the actual position of the target is small, and the positioning is accurate.
in this embodiment, in a first aspect, each infrared sensor node may include 6 infrared sensors, and in a case where hardware resources are fixed, the size of the acquisition range of the infrared sensor node is effectively controlled by an annular uniform layout manner of the 6 infrared sensors, and the positioning accuracy is improved. And in the second aspect, positioning is carried out based on the angle, and the positioning precision can be changed by adjusting the angle and the position of the infrared sensor node, so that the flexibility and the expandability of the system are improved. In the third aspect, data of a plurality of sensors are fused, so that the reliability of target positioning is enhanced.
corresponding to the above method embodiment, an embodiment of the present invention further provides a target positioning method, which may be applied to a positioning device in a target positioning system, as shown in fig. 1, where the system includes: a plurality of infrared sensor nodes (infrared sensor node 1 … … infrared sensor node M, M being a positive integer greater than 1) 100 and a positioning device 200; each infrared sensor node 100 includes a plurality of infrared sensors (infrared sensor 1 … …, infrared sensor N, N being a positive integer greater than 1) 110 and a processor 120 connected to the plurality of infrared sensors. As shown in fig. 12, the method may include:
S1201: receiving range information of a target sent by a processor of each infrared sensor node; the range information is determined by the processor according to infrared signals collected by a plurality of infrared sensors connected with the processor.
For example, the system may include 9 infrared sensor nodes, as shown in fig. 4, the 9 infrared sensor nodes may be uniformly arranged in 3 rows and 3 columns, or 8 infrared sensor nodes are uniformly arranged in a rectangle, and the other 1 infrared sensor node is located at the center of the rectangle. Fig. 4 is merely an example, and the number and the arrangement shape of the infrared sensor nodes are not limited, for example, the 8 infrared sensor nodes may be uniformly arranged in a circumferential shape.
For example, each infrared sensor node may include 6 infrared sensors, and in one case, the 6 infrared sensors may be arranged in a circumferential shape. As shown in fig. 3, the acquisition range of the 6 infrared sensors is divided into 12 detection regions, wherein (c) - (c) in fig. 3 represent the numbers of the infrared sensors, and (a) - (L) represent the numbers of the detection regions. In fig. 3, the acquisition ranges of adjacent infrared sensors intersect with each other, and the intersecting range is called an overlap region, for example, A, C, E, G, I, K, which are 6 detection regions are overlap regions, B, D, F, H, J, L, which are non-overlap regions.
in one embodiment, the range information of the target may be a number of a detection region where the target is located. In this way, the processor of each infrared sensor node sends the determined number of the detection area to the positioning device 200, and the positioning device 200 determines the specific position of the target by using a data fusion algorithm based on the number of the detection areas.
Or, in another embodiment, the detection region information may be angular bisector information of the detection region, so that the processor of each infrared sensor node sends the determined angular bisector information of the detection region where the target is located to the positioning device 200, the positioning device 200 determines a plurality of angular bisector intersection points based on the angular bisector information, and fuses the angular bisector intersection points by using a data fusion algorithm to obtain the specific position of the target.
s1202: and performing fusion processing on the received range information by using a data fusion algorithm to obtain the position of the target.
as described above, the positioning device 200 determines a plurality of angle bisector intersection points, and fuses the angle bisector intersection points by using a data fusion algorithm to obtain a specific target position. Taking an object as an example, the pointing device 200 may determine the location of the object based on the midpoint of the intersection of these bisectors. For example, in one embodiment, a center value method may be used, and the locating device 200 may determine the midpoint of the intersection of the bisectors as the location of the target.
for another example, in another embodiment, a loop elimination method may be adopted, and the positioning apparatus 200 may determine a midpoint of the intersection points of the angle bisectors, then eliminate the intersection points of the angle bisectors whose distance from the central point is greater than a preset threshold, and return to the step of determining the midpoint of the intersection points of the angle bisectors, until the central point is determined as the position of the target when the distance between each intersection point of the angle bisectors and the central point is less than or equal to the preset threshold. In the embodiment, the edge points are repeatedly eliminated, the central point is repeatedly determined, and the positioning accuracy is improved.
In one embodiment, the plurality of infrared sensor nodes include a central node and a plurality of peripheral nodes; each infrared sensor node forms a plurality of detection areas; the range information is angular bisector information of the detection area; s1202 may include:
determining an intersection point of the angular bisector corresponding to the central node and the angular bisector corresponding to the peripheral node as a first intersection point according to angular bisector information sent by a processor of each infrared sensor node; determining an intersection point of the angle bisectors corresponding to the plurality of peripheral nodes as a second intersection point;
Clustering the first intersection point to obtain a first clustering result;
Clustering the second intersection points based on the first clustering result to obtain a second clustering result, and determining one or more targets according to the second clustering result;
For each target, a center point of an intersection of the bisectors associated with the target is determined, and a location of the target is determined based on the center point.
as an embodiment, for each target, determining a center point of an intersection of angle bisectors associated with the target, and determining a position of the target based on the center point may include:
For each target, determining a central point of an intersection point of angle bisectors associated with the target, and determining the central point as the position of the target;
Alternatively, the first and second electrodes may be,
for each target, determining a center point of an intersection point of the angle bisectors associated with the target;
And eliminating angular bisector intersection points of which the distance between the angular bisector intersection points and the central point is greater than a preset threshold value from the angular bisector intersection points associated with the target, and returning to the step of determining the central point of the angular bisector intersection points associated with the target until the central point is determined as the position of the target under the condition that the distance between each angular bisector intersection point and the central point is less than or equal to the preset threshold value.
Generally, after an object enters the acquisition range of the infrared sensor node, the central node can detect the object. In this embodiment, clustering is performed based on the first intersection point, that is, clustering is performed based on the intersection point of the angular bisector associated with the center node, and then clustering is performed on the intersection points of the other angular bisectors based on the clustering result. Therefore, compared with clustering based on intersection points of all angle bisectors, the method has the advantages of smaller calculated amount and more accurate clustering result.
if a plurality of targets are determined by the clustering result, each target can be positioned respectively. As described above, the positioning apparatus may position the target by using a median method or a cyclic elimination method. If the center value method is adopted, in this embodiment, the positioning apparatus 200 may determine, for each object, a center point of an intersection of bisectors associated with the object, and determine the center point as the position of the object.
if the loop elimination method is adopted, in the embodiment, the positioning apparatus 200 may determine, for each object, a center point of an intersection point of bisectors of angles associated with the object; and eliminating angular bisector intersection points of which the distance between the angular bisector intersection points and the central point is greater than a preset threshold value from the angular bisector intersection points associated with the target, and returning to the step of determining the central point of the angular bisector intersection points associated with the target until the central point is determined as the position of the target under the condition that the distance between each angular bisector intersection point and the central point is less than or equal to the preset threshold value.
the method of the foregoing embodiment is used to implement the corresponding system in the foregoing embodiment, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.
those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the idea of the invention, also features in the above embodiments or in different embodiments may be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity.
In addition, well known power/ground connections to Integrated Circuit (IC) chips and other components may or may not be shown within the provided figures for simplicity of illustration and discussion, and so as not to obscure the invention. Furthermore, devices may be shown in block diagram form in order to avoid obscuring the invention, and also in view of the fact that specifics with respect to implementation of such block diagram devices are highly dependent upon the platform within which the present invention is to be implemented (i.e., specifics should be well within purview of one skilled in the art). Where specific details (e.g., circuits) are set forth in order to describe example embodiments of the invention, it should be apparent to one skilled in the art that the invention can be practiced without, or with variation of, these specific details. Accordingly, the description is to be regarded as illustrative instead of restrictive.
While the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. For example, other memory architectures (e.g., dynamic ram (dram)) may use the discussed embodiments.
The embodiments of the invention are intended to embrace all such alternatives, modifications and variances that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, substitutions, improvements and the like that may be made without departing from the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. An object positioning system, comprising: a plurality of infrared sensor nodes and a positioning device; each infrared sensor node comprises a plurality of infrared sensors and a processor connected with the plurality of infrared sensors;
The infrared sensor is used for acquiring infrared signals;
the processor is used for determining range information of a target according to infrared signals collected by a plurality of infrared sensors connected with the processor, and sending the determined range information to the positioning equipment;
And the positioning equipment is used for carrying out fusion processing on the range information sent by the processor of each infrared sensor node by using a data fusion algorithm to obtain the position of the target.
2. the system of claim 1, wherein the processor is specifically configured to:
aiming at each infrared sensor connected with the infrared sensor, acquiring an infrared signal acquired by the infrared sensor and acquiring incremental data corresponding to the infrared signal; generating an event signal corresponding to the infrared sensor based on the infrared signal and the incremental data, wherein the event signal is a signal indicating whether a target is detected or not;
and determining range information of the target according to the generated event signal corresponding to each infrared sensor, and sending the determined range information to the positioning equipment.
3. The system according to claim 2, wherein each infrared sensor node comprises N infrared sensors uniformly arranged in the circumferential direction, N is a positive integer greater than 1, the N infrared sensors form 2N detection regions, the 2N detection regions comprise N overlapping regions and N non-overlapping regions, the overlapping regions are regions where the acquisition ranges of adjacent infrared sensors overlap, and the non-overlapping regions are regions where the acquisition ranges of adjacent infrared sensors do not overlap;
The processor is further configured to: and determining the detection area information of the target according to the generated event signal corresponding to each infrared sensor, and sending the determined detection area information to the positioning equipment.
4. the system of claim 3, wherein the processor is further configured to:
If a plurality of candidate detection areas are determined according to the generated event signal corresponding to each infrared sensor, determining the probability of the target existing in each candidate detection area;
and determining the detection region information of the target based on the probability corresponding to each candidate detection region.
5. The system according to claim 4, wherein the information of the detection area where the target is located is: information of an angular bisector of a detection area where the target is located; the plurality of infrared sensor nodes comprise a central node and a plurality of peripheral nodes; the positioning device is further configured to:
Determining an intersection point of the angular bisector corresponding to the central node and the angular bisector corresponding to the peripheral node as a first intersection point according to angular bisector information sent by a processor of each infrared sensor node; determining an intersection point of the angle bisectors corresponding to the plurality of peripheral nodes as a second intersection point;
clustering the first intersection point to obtain a first clustering result;
clustering the second intersection points based on the first clustering result to obtain a second clustering result, and determining one or more targets according to the second clustering result;
for each target, a center point of an intersection of the bisectors associated with the target is determined, and a location of the target is determined based on the center point.
6. the system according to claim 5, wherein the positioning device is specifically configured to:
For each target, determining a central point of an intersection point of angle bisectors associated with the target, and determining the central point as the position of the target;
Alternatively, the first and second electrodes may be,
for each target, determining a center point of an intersection point of the angle bisectors associated with the target;
and eliminating angular bisector intersection points of which the distance between the angular bisector intersection points and the central point is greater than a preset threshold value from the angular bisector intersection points associated with the target, and returning to the step of determining the central point of the angular bisector intersection points associated with the target until the central point is determined as the position of the target under the condition that the distance between each angular bisector intersection point and the central point is less than or equal to the preset threshold value.
7. The system of claim 6, wherein each infrared sensor node comprises 6 infrared sensors, the 6 infrared sensors are arranged in a circular shape, the plurality of peripheral nodes are 8 infrared sensor nodes arranged in a rectangle, and the central node is located at the center of the rectangle.
8. The target positioning method is characterized by being applied to positioning equipment in a target positioning system, wherein the system comprises a plurality of infrared sensor nodes and the positioning equipment; each infrared sensor node comprises a plurality of infrared sensors and a processor connected with the plurality of infrared sensors; the method comprises the following steps:
receiving range information of a target sent by a processor of each infrared sensor node; the range information is determined by the processor according to infrared signals collected by a plurality of infrared sensors connected with the processor;
And performing fusion processing on the received range information by using a data fusion algorithm to obtain the position of the target.
9. the method of claim 8, wherein the plurality of infrared sensor nodes comprises a central node and a plurality of peripheral nodes; each infrared sensor node forms a plurality of detection areas; the range information is angular bisector information of the detection area;
The using a data fusion algorithm to perform fusion processing on the received range information to obtain the position of the target includes:
determining an intersection point of the angular bisector corresponding to the central node and the angular bisector corresponding to the peripheral node as a first intersection point according to angular bisector information sent by a processor of each infrared sensor node; determining an intersection point of the angle bisectors corresponding to the plurality of peripheral nodes as a second intersection point;
clustering the first intersection point to obtain a first clustering result;
Clustering the second intersection points based on the first clustering result to obtain a second clustering result, and determining one or more targets according to the second clustering result;
For each target, a center point of an intersection of the bisectors associated with the target is determined, and a location of the target is determined based on the center point.
10. The method of claim 9, wherein for each object, determining a center point of an intersection of bisectors associated with the object, determining a location of the object based on the center point, comprises:
For each target, determining a central point of an intersection point of angle bisectors associated with the target, and determining the central point as the position of the target;
Alternatively, the first and second electrodes may be,
For each target, determining a center point of an intersection point of the angle bisectors associated with the target;
and eliminating angular bisector intersection points of which the distance between the angular bisector intersection points and the central point is greater than a preset threshold value from the angular bisector intersection points associated with the target, and returning to the step of determining the central point of the angular bisector intersection points associated with the target until the central point is determined as the position of the target under the condition that the distance between each angular bisector intersection point and the central point is less than or equal to the preset threshold value.
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