DE102017121950A1 - A method of estimating a state of a mobile platform - Google Patents

Abstract

A method (500) for determining a state of a movable platform with respect to a reference surface is provided. The method comprises the steps of: detecting (510) a first distance value (30) between the movable platform (10) and the reference surface (20); Determining (520) a second distance value (55) between the movable platform (10) and the reference surface (20) based on a model of the reference surface and a position of the movable platform relative to the reference surface, the second distance value (55) being the smallest distance between the reference surface and the movable platform; Determining (530) a difference between the first distance value (30) and the second distance value (55); Using (540) the difference as a residual and evaluating the residual to match a map of a state of the moveable platform to the state of the moveable platform.

Description

Field of the invention

The application relates to a method for determining a state of a movable platform with respect to a reference surface, a state determination unit for a mobile platform implementing the said method, and a mobile platform having such a state determination unit.

Technical background

In aviation, in particular, it may be of great importance to determine a position or, more generally, a state of an aircraft (in general: a mobile platform) with respect to the first surface and to propagate a progression of this state. For this purpose, an image of the overflown terrain is usually used as well as measurement results of sensors on board the aircraft.

For example, so-called terrain reference navigation (TRN), which is a terrain data-assisted navigation method, can be used. A two-dimensional or three-dimensional navigation solution is determined by comparing the overflow terrain with a digital terrain model carried onboard the aircraft. A sensor (for example, a radar altimeter) scans the overflown terrain and determines a profile of the terrain as well as a distance between the aircraft and the terrain.

Summary

It can be considered an object of the invention to provide a method for determining a state of a movable platform, which is characterized by an increased accuracy of the determined state.

According to a first aspect, a method for determining a state of a movable platform with respect to a reference surface is provided. The method comprises the steps of: detecting a first distance value between the movable platform and the reference surface; Determining a second distance value between the movable platform and the reference surface based on a model of the reference surface and a position of the movable platform relative to the reference surface, the second distance having the smallest distance between the reference surface and the movable platform; Determining a difference between the first distance value and the second distance value; Using the difference as a residual and evaluating the residual to match a map of a state of the moving platform to the state of the moving platform.

The mobile platform may in particular be an aircraft, but also a watercraft and may also be referred to as a mobile platform. In the context of the description, these terms are understood as synonyms.

The detection of the first distance value can take place, for example, with a radar system on board the aircraft or with another sensor. The second distance value is determined based on a model or a map of the reference area (in particular the earth's surface) and a position of the mobile platform with respect to the model of the reference area. Subsequently, the difference between the detected distance value and the determined distance value is determined. Then this difference is used to match a map, in particular a mathematical map, of the state of the mobile platform to a real state of the mobile platform.

Matching the mapping of the state of the mobile platform to the actual state is done with the goal that mapping and reality run in parallel, for example because the mapping of reality can be buggy and requires correction. This equalization takes place, for example, by means of a Kalman filter, wherein the imaged state is tracked to the real state via the evaluation of a residual for the Kalman filter. It should be noted that a Kalman filter does not necessarily have to be used. Rather, other methods that use a terrain reference navigation can be used.

A Kalman filter implements a method for solving non-linear estimation problems and may also be referred to as a minimum variance estimator. In order to be able to track a (mathematical) representation of reality, the Kalman filter needs a so-called residuum. To determine this residual, the detected first distance value is compared to the determined second distance value.

In principle, the Kalman filter can be used to track a movement sequence of the movable platform and to make forecasts or estimates about the movement sequence (for example relative to the reference surface) for the future. Typically, a Kalman filter forecasts the evolution of the distance between the movable platform and the reference surface, based on historical ones Data, ie the previous movement or distance between the movable platform and the reference surface.

When a radar system is used to acquire the first distance value, the detected first distance value due to the signal processing in a radar altimeter corresponds to the shortest distance between the radar system (or the aircraft containing the radar system) and the terrain surface. In contrast, the determined second distance value corresponds to the vertical distance between the mobile platform and the terrain surface in the terrain model or in the image of the reference area.

It has been recognized that in determining the residual, a comparison of the shortest distance between the aircraft and the terrain surface (the detected first distance value) with the vertical distance between the aircraft and the terrain surface image (the determined second distance value) may result in inaccuracy. This is especially the case when the point of the terrain surface with the shortest distance to the aircraft and the point vertically below the aircraft are not identical. In this case, a comparison between the first distance value and the second distance value may result in a residual that makes the difference between the mapping of reality and reality greater than it actually is. For the sake of completeness, reference is made to a special case in which the shortest distance also corresponds to the vertical height of the aircraft over ground: this is the case when the aircraft is flying over a flat, horizontal terrain. For all other types of terrain, this relationship is not necessarily given.

Based on this finding, it is proposed not to choose the vertical height of the aircraft with respect to the terrain surface in the terrain model for the determination of the residual as a second distance value, but instead to determine the shortest distance between the aircraft and the terrain surface in the terrain model and Compare this shortest distance, which was determined on the basis of the terrain model, with the detected first distance value to determine the residual.

In an embodiment it is provided that the method further comprises the step of: determining a reference point of the reference surface in the model of the reference surface based on the position of the movable platform with respect to the model of the reference surface, the reference point of the movable platform being the smallest distance between the reference surface Reference surface and the movable platform has.

In other words, this step of the method means that, instead of the vertical height of the movable platform above the reference surface, the distance to that point of the reference surface is determined which is spatially nearest to the movable platform, that is to say based on the information about the course of the terrain in one Three-dimensional coordinate system of the illustration of the terrain (of the terrain model). This avoids a systematic error in the determination of the residual and does not compare distances to different points on the terrain surface, but both the distance detected by the radar system and the distance determined in the terrain model refer to that point which the aircraft is closest.

According to one embodiment, the method further comprises the following step: determining a tangential plane which bears against the reference point so that a connecting line between the movable platform and the reference point intersects the tangential plane perpendicularly. Preferably, the connecting line is orthogonal on the tangential plane.

By doing so, the tangent plane is provided as an approximation to the surface of the reference surface, starting from the reference point. In other words, there is a linearization of the reference surface. With this linearization, the process can be carried out more easily or at all. Because the connection line is perpendicular to the tangent plane, the connection line also corresponds to a direct line of sight from the sensor / radar system (the terms sensor and radar are used synonymously herein) to the reference point closest to the sensor.

The radar system is characterized by a certain club width and has a correspondingly limited search angle range. The closest point of the reference surface with respect to the mobile platform determined by the radar system is always within the search angle range. The size of the search angle range may vary depending on the distance between the mobile platform and the reference surface. In any case, it is sufficient to dimension the size of the tangential plane in the terrain model so that it corresponds to the search angle range of the radar system on the real earth surface. The reason for this is that linearization of the terrain outside of the search angle range is simply not necessary.

In other words, the tangent plane is used within the search angle range of the radar. This area of the tangential plane is referred to as a tangential surface and has an extent or size that depends, inter alia, on the radar geometry / radar lobe, flight altitude, terrain course. The tangential surface is thus approximately as large as the search angle range of the radar, preferably at least as large as the search angle range of the radar, more preferably exactly the same size as the search angle range of the radar.

A Kalman filter can be used to estimate a development of the distance between the movable platform and the reference surface based on the tangent plane. However, such an estimate is more reliable if a distance between the tangent plane and the reference surface does not become too large, i. does not exceed a respective threshold or, generally speaking, the tangent plane does not deviate too much from the reference surface.

According to a further embodiment, the method further comprises the following step: comparing the tangential plane with the model of the reference surface in a predetermined region of the model of the reference surface.

In other words, the tangent plane is compared with the terrain area (part of the model of the reference area) which corresponds to the search angle area of the radar or a part thereof. Conversely, this means that deviations of the tangential plane from the model of the reference surface outside the predetermined terrain area for this comparison need not be considered or not taken into account.

The tangent plane is compared with the model of the reference surface to determine the accuracy of the linearization (ie the simplified representation of the reference surface as a plane) for different areas of the reference surface, so that it can be determined in which terrain areas are reliably worked with the tangent plane as linearization can.

According to another embodiment, the method further comprises the step of: determining a respective deviation value between the model of the reference surface and the tangent plane for each point of a plurality of predetermined points in the model of the reference surface.

Preferably, the reference surface is present as a discrete terrain model and has a plurality of terrain points with associated data (coordinates of the terrain points in a coordinate system of the terrain model, as well as other properties of the terrain, which are assigned to the terrain points). These points are used to determine a distance between the terrain model and the tangent plane.

According to another embodiment, the method further comprises the step of: determining the number of deviation values between the model of the reference surface and the tangent plane exceeding a predetermined deviation threshold; and discarding the detected first distance value if the number of deviation values exceeding the predetermined deviation threshold exceeds a predetermined threshold for that number.

This embodiment makes it possible to determine the terrain roughness or the non-linearity of the terrain (ondulation). If the nonlinearity exceeds a certain amount, the detected first distance value is not used because the terrain within the search angle range deviates too much from the linear terrain model (the tangent plane). The reason for this is, among other things, that in a very rough terrain can not always be clearly determined, which is the nearest point, which has detected the radar. This is mainly due to tolerances and measurement inaccuracies of the radar system. From this, an inaccuracy could be introduced into the method because the distance detected by the radar could undesirably deviate from the distance determined by the terrain model to the nearest point of the terrain surface to the mobile platform.

According to another embodiment, said steps are carried out in a repetitive process as long as the movable platform is in motion.

In other words, the method is executed by a computer using the necessary data, and the steps of the method are repeated so that the state of the mobile platform is always redetermined.

According to a further embodiment, the first distance value between the movable platform and the reference surface is detected by means of a radar system.

According to another embodiment, the movable platform is an aircraft, and the reference surface corresponds to the earth's surface, and the model of the reference surface is a terrain database.

By means of a radar system on board the aircraft, the distance to the earth's surface is detected. In addition, the position of the aircraft with respect to the earth's surface is determined, for example by means of a navigation system, such as a satellite-based navigation system. The determined position of the aircraft is converted into coordinate values of a map of the earth's surface or a model of the earth's surface (eg a terrain database). With the aid of these coordinate values, it is possible to determine in the model of the earth's surface which point of the earth's surface (in the model) is closest to the position of the aircraft. The distance detected by the radar system and the distance determined by the model are compared and the difference used as a residual for a Kalman filter to detect or monitor the condition of the aircraft.

Aspects of the method and considerations on which the method is based can be summarized as follows:

The error covariance calculation is performed in the Kalman filter with the error model linearized around the operating point. The minimization of the error covariance matrix then leads to the searched time-variant optimal filter gain matrix, which is used both for correcting error covariance matrix and for correcting the navigation state vector. In other words, the state of the platform in the model is checked as a function of the detected physical knife values and corrected if necessary.

The use of a Kalman filter method requires a linear system dynamics and measurement equation in addition to centered and Gaussian distributed system noise. Any non-linearities in the system dynamics or in the measurement equation can always lead to a deterioration of the expected accuracy and can represent an integrity problem.

For the use of the Kalman filter method, it is necessary to substitute the non-linear height model of the earth's surface (ie the reference surface) at the operating point by a linearized model. This is done by determining a tangential plane which is present at the reference point (also: touch point).

The point of contact that indicates the shortest distance between the aircraft and the terrain surface forms the operating point. The linearized model of the earth's surface (the tangential plane) is described mathematically by a plane equation that defines a plane tangent to the Earth's surface at the working point.

The method determines the difference of the non-linear terrain model and the tangent plane (the deviation of the tangential plane from the terrain model, the deviation values) and compares this difference against a defined tolerance limit. Each individual deviation value is first compared with a deviation threshold value to determine whether the deviation in one point exceeds the threshold value. Then, the number of points that exceed this threshold is then determined. If this number is too high, the measurement of the first distance between the aircraft and the earth's surface by the radar will not be used, because too much inaccuracy is to be expected.

Alternatively, the differences in the Kalman filter may be taken into account as increased inaccuracy. An inadequate agreement between linear and non-linear altitude model of the earth's surface indicates a strong ondulation (unevenness of the terrain surface, terrain inaccuracy) of the terrain.

Excessive terrain inaccuracy will result in too large a variance in the formation of the residual from the radar altitude reading and the mathematically determined shortest distance between the aircraft position and the terrain surface (in the model). The effects are similar to the systematic error in comparing the radar altimeter skew distance (the distance measured by the radar installation between the aircraft and the nearest point) and the vertical distance between the aircraft and the earth's surface.

A conservative approach would exceed the tolerance limit (the number of deviation values exceeding the deviation threshold), discard the currently available radar altitude measurement, or lead to a degradation of the modeled radar altitude accuracy. This will ensure that the Kalman filter uses only radar altimetry to form the residual, as the basis for determining the covariances correction and system states, for which the deviation between the linear and nonlinear terrain model is acceptable.

In addition to the determination of the skew distance tolerance, the tolerance of the oblique distance direction (normal of the plane) can additionally be determined. If this tolerance exceeds a limit value, the measurement can also be discarded.

The method is characterized in that an oblique distance (shortest distance between aircraft and terrain surface) is determined using a digital terrain database and (together with the distance value detected by the radar system) is used for the determination of the residual. In addition, the accuracy of the linear map (the tangential plane) of the terrain surface is monitored so as not to exceed a tolerance limit between the non-linear and the linear terrain model with respect to skew distance and skew distance direction.

In another aspect, a mobile platform state determination unit is provided. The state determination unit comprises: a data memory for holding a model of a reference area; a position detecting unit for detecting the position of the mobile platform with respect to a reference surface; and a distance detecting unit for detecting a distance of the mobile platform from the reference surface; wherein the state determination unit is configured to carry out the method according to one of the embodiments described above.

In particular, the state determination unit can have a processor which can be linked via interfaces with sensors of the aircraft and with a model of the earth's surface. In this case, the processor is executed to carry out the method described above. The above-described steps of the method can be implemented as functions of the processor. Although these steps are not repeated at this point individually, it follows that these are also disclosed in combination with the state determination unit due to this back reference.

The processor may be a processor that meets requirements for the intended use environment of an aircraft. The processor may be a single core or multi-core processor. The terrain database may be a data store which is designed to store data stored therein permanently or over a long period of several years, even without connection to a power source and also without the state determination unit being in operation.

In another aspect, a mobile platform is provided with a state determination unit as described above.

The mobile platform may be an aircraft, a land vehicle or a watercraft.

Basically, the state determination unit and method as described herein may be used in any vehicle in which a state is based on measurement results from sensors (eg, the distance to an object or point of the environment detected by a radar) and a map of the surroundings of the vehicle Vehicle must be reliably determined. In an aircraft, the distance and position / attitude / orientation to the earth's surface are relevant. In a land vehicle, this may be the relative position with respect to an object (building, environmental object). In the case of a watercraft, this may be similar to the aircraft, the distance and the relative position to the bottom of the water or a seabed, the ground may also be understood as earth surface or reference surface and insofar resembles the constellation in an aircraft. The vessel may be an overwater vehicle (ship) or an underwater vehicle (submarine). In both cases, it is important to know a distance to the ground.

list of figures

• 1 eine schematische Darstellung eines Luftfahrzeugs und einer Referenzfläche gemäß einem Ausführungsbeispiel;
• 2 eine schematische Darstellung eines Luftfahrzeugs und einer Referenzfläche gemäß einem weiteren Ausführungsbeispiel;
• 3 eine schematische Darstellung einer Zustandsermittlungseinheit gemäß einem weiteren Ausführungsbeispiel;
• 4 eine schematische Darstellung einer Zustandsermittlungseinheit gemäß einem weiteren Ausführungsbeispiel;
• 5 eine schematische Darstellung der Schritte eines Verfahrens gemäß einem weiteren Ausführungsbeispiel.

In the following, embodiments of the invention will be described with reference to the figures. Show:

• 1 a schematic representation of an aircraft and a reference surface according to an embodiment;
• 2 a schematic representation of an aircraft and a reference surface according to another embodiment;
• 3 a schematic representation of a state determination unit according to another embodiment;
• 4 a schematic representation of a state determination unit according to another embodiment;
• 5 a schematic representation of the steps of a method according to another embodiment.

Detailed description of embodiments

The illustrations in the figures are schematic and not to scale. If the same reference numerals are used in the following description of the figures, these relate to the same or similar elements.

1 shows a schematic representation of an aircraft 10 (also: mobile or mobile platform) with reference to a reference surface 20 , The reference surface 20 corresponds to the Earth's surface or a model thereof. For the purposes of air traffic operations of the aircraft 10 must be the condition of the aircraft 10 be determined and updated on an ongoing basis. This state of the aircraft may be, for example, a position, orientation, position, speed, as well as other operating parameters with or without reference to the reference surface 20 Respectively.

On board the aircraft 10 There is typically a radar system (in 1 Not shown). The radar system determines a first distance value at predetermined or periodic time intervals 30 to the reference surface 20 , This first distance value is usually the shortest distance to the reference surface since a radar system inherently is the closest object within the search angle range of the radar lobe 15 (dashed lines taken from the aircraft 10 go out). In the example of 1 this closest point is the reference point 40 , The reference point 40 lies on the reference surface 20 , No other area of the reference surface 20 is closer to the aircraft 10 , as can be seen in the circular arc shown in broken lines, which with the shortest distance as the radius around the aircraft 10 is laid.

However, with knowledge of the first distance value 30, it is only known how close the aircraft is 10 any area (the reference point 40 ) is the reference surface, but it is not known exactly where the aircraft 10 located with reference to the reference surface. In order to determine this information, the first distance value is used to determine the position / attitude / orientation of the aircraft (in general: state of the aircraft) in a model of the reference surface or to update an image of the aircraft in the model. In order to keep the picture up to date, a position of the aircraft becomes 10 determined in the model and based on this determined position of the aircraft in the model, a distance to the reference surface (this is the second distance value) determined. The first distance value and the second distance value are compared with each other and the difference between these two distance value one serves as a residuum for a Kalman filter.

For purposes of illustration, is in 1 furthermore the vertical distance or the vertical height 60 of the aircraft 10 above the reference surface 20 shown. It can be seen that the vertical height 60 in the case of uneven terrain deviates significantly from the shortest distance to the reference surface. This difference between the vertical height 60 and the detected shortest distance 30 can be considered a systematic mistake 65 be designated. In order to reduce or even completely eliminate this systematic error, it is proposed in the present case that in the model of the reference surface, not the vertical height 60 determined in the aircraft and used for the determination of the residual, but that in the model of the reference surface also the shortest spatial distance between the aircraft 10 and the reference surface 20 is determined. This shortest distance can be determined in the model, for example, by means of a 3-dimensional coordinate system in which the aircraft 10 and points of the reference surface 20 in each case a coordinate value is assigned. Regardless of whether the detected by the radar system distance value (first distance value 30 ) the distance value determined by calculation in the model (second distance value 55 ) is determined by the use of the second distance value 55 as the shortest spatial distance in the model instead of the vertical height 60 avoided the systematic error described above and the residual for the Kalman filter is determined with a higher reliability.

2 shows the representation of 1 supplemented by the tangential plane 70 which by the reference point 40 runs or rests against this. The tangential plane 70 can also be referred to as a linearized terrain area or linearization. This linearization is necessary in order to be used as input value for the Kalman filter. As though out 2 can be seen has the tangent plane 70 in some places a greater distance than at other places. This distance of the tangential plane 70 from the reference surface 20 may be referred to as a linearization error.

Preferably, the data, which is the reference surface 20 in the model, in discrete form, such that, for example, in a 3-dimensional coordinate system to individual points of the reference surface 20 the corresponding coordinates are kept. The tangential plane 70 may also be in discrete form, but it may also be described by means of a mathematical equation. Based on this information can be for each point of the reference surface 20 a distance to the tangential plane 70 be calculated. This distance is also called the deviation value 80 designated. For a plurality of deviation values of 80, it can be determined how many individual values of these plurality of deviation values exceed a threshold value for the distance (the deviation of the tangential plane from the reference surface). Basically, the more deviation values exceed the threshold for the distance, the greater the roughness of the terrain or the reference surface 20 (the ondulation). There may be reasons to ignore readings in very rough terrain, because the risk of measurement errors and the uncertainty as to which point of the reference surface the radar has detected are large. Thus, also a comparison of the detected first distance value with the second distance value determined in the model would possibly introduce a systematic error because the distances to different points of the reference surface would be used.

3 shows a schematic representation of a state determination unit 300 which data from an inertial navigation system or an inertial navigation system 305 as well as a radar system 310 to update a state of an aircraft or other movable platform in a model. The state determination unit 300 is based on the basic structure of the architecture of the Luenberger observer.

The state determination unit 300 has an arithmetic unit 410 shown with a dashed line. The arithmetic unit 410 For example, it may be a processor that can execute instructions. The arithmetic unit 410 contains various functional modules. These functional modules may be implemented as hardware modules or software modules or combinations thereof. The arithmetic unit 410 is executed, the method described herein or its steps (see also 5 ).

A moving platform moves in a real environment. The movement of the mobile platform can be done with the inertial navigation system 305 be recorded. Likewise, by means of the radar system 310 a relative position of the movable platform to the environment (in the case of an aircraft, this is, for example, the earth's surface or the reference surface described above 20 ). With these two pieces of information, the position and / or a state of the movable platform can be tracked and updated in a picture of the real environment.

For the purpose of updating the model, those of the inertial navigation system 305 received data via a movement of the movable platform of an input matrix 315 fed. The of the radar system 310 detected first distance values are also the arithmetic unit 410 fed. The arithmetic unit 410 determines a difference between a first distance value from the radar system and a second distance value, which was determined based on the model of reality and a position of the movable platform in this model. This difference becomes a Kalman filter 320 supplied as a residuum and serves to track the position of the movable platform and its state in the model of reality.

For the control of dynamic systems with the aid of state control, the measurability of all state variables of the controlled system is a prerequisite. In real systems, it is often not possible, or only by an increased effort, to record all state variables metrologically.

The Luenberger observer (condition observer) makes it possible to reconstruct non-measurable or only extensively measurable states of a dynamic system. For this purpose a model of the system is kept parallel to a real dynamic system.

The dynamic behavior of a real system is described in the state space representation by two equations, namely the so-called state differential equation and the output equation. 3 shows schematically and in an example the linkage of the state variables, the input variables (Modul 315 ) and the output variables (modul 335 ) of a state differential equation and an output equation in a state space representation.

The dynamics of the real system is in the system matrix (Modul 330 ). The system matrix (module 330 ) describes the temporal change of the individual parameters of the state vector x. The solution of the state differential equation takes place in the integrator (Modul 325 ).

Overall, the state determination unit supplies 300 an output value 415 indicating the state of the movable platform in the model. This output value 415 For each step of the method, it contains an updated (new) state vector x, for example with the parameters position, position, velocity, etc. The composition of the state vector corresponds to that in the system matrix 330 modeled parameters.

The functionality of in 3 shown state determination unit 300 can be further described as follows: The integrator (module 325 ) solves the state differential equation. The new, updated values of all states are now known and can be used for a wide variety of applications. The state vector is included at the output of the module 325 concrete values for the parameters of the state vector, eg via the states velocity or position, etc. From these values of the state vector, in the measurement matrix 335 the value for the shortest distance between aircraft and terrain can be calculated.

The entire state vector with all its parameters can be corrected with only a single measured value (eg resulting from a radar altimeter). This is called reconstruction of the state vector. The fact that a single measured value is sufficient is due to the system matrix 330 ensured. Here is the mathematical relationship between Radarhöhenmesswert and position, speed or position, etc. described or modulated.

4 shows an exemplary representation of the state determination unit 300 , The arithmetic unit 410 is on the one hand with a group of sensors 420 and on the other hand with a data storage 430 each coupled via suitable interfaces. The group of sensors 420 contains, for example, a position determination unit 422 and a distance detection unit 424 , The position determination unit 422 For example, a satellite-based navigation system is used to determine a position of the movable platform with respect to the environment of the mobile platform. The distance detection unit 424 can as a radar system 310 (please refer 3 ).

The sensors 420 serve to determine a position of the movable platform relative to the environment. For example, the sensors determine 420 the first distance value 30 as the shortest distance between the moving platform 10 and the reference surface 20 , where the shortest distance is at a reference point 40 refers to which of the mobile platform 10 is closest. This relationship is indicated by a schematic representation of the movable platform 10 as well as the reference surface 20 below the rectangle, which the sensors 420 represents. This representation is the real environment.

In the data store 430 For example, a map of the environment or a model of reality is provided which is, for example, a terrain database with information about the structure of a terrain section or part of the earth's surface. The arithmetic unit 410 is executed, a position and a state of the movable platform 10 to update and maintain in relation to the model of reality. In other words, this model indicates where and how the movable platform is located with respect to the model of reality. This model illustration is also by a schematic representation of the movable platform 10 as well as the reference surface 20 which the data store 430 represents, indicated. In the model or with the help of the model becomes the second distance value 55 which also determines the shortest spatial distance between the movable platform 10 and the reference surface 20 indicates.

The first distance value 30 , which was detected in reality, and the second distance value 55 , which was determined in the model of reality, are compared with each other to indicate a residue for a Kalman filter, the residual serving to update the map of reality or the model of reality.

5 shows a schematic representation of the steps of a method 500 for determining a state of a movable platform with respect to a reference surface.

In a first step 510 becomes a first distance value 30 between the movable platform 10 and the reference surface 20 detected. In a second step 520, a second distance value 55 between the movable platform 10 and the reference surface 20 determined based on a model of the reference surface and a position of the movable platform relative to the reference surface. In a third step 530, a difference between the first distance value 30 and the second distance value 55 certainly. In a fourth step 540 the difference is used as a residual and the residual is evaluated to match a map of a state of the moving platform to the actual state of the moving platform. In a fifth step 550 becomes a reference point 40 of the reference surface in the model of the reference surface based on the position of the movable platform relative to the model of the reference surface or in the image of the reality, wherein the reference point of the movable platform has the smallest distance between the reference surface and the movable platform.

In order to determine the second distance value in the model of reality, the position of the movable platform is necessary. This position is determined and provided by a position determination unit. Thus, the position can be used to determine in the model of reality, starting from the position of the movable platform closest to this position point of the reference surface.

For example, the position of the movable platform may be coordinates in a coordinate system. The position can be specified for example in a coordinate system of the earth.

The method can be used to particular advantage in an aircraft to estimate the evolution of the distance of the aircraft to the earth's surface. It is a particular aspect that the measured or detected shortest distance between the aircraft and the earth's surface and the shortest distance determined by means of a model of the earth's surface and the position of the aircraft are compared with one another. Then, a reference point on the earth's surface can be determined, which has the shortest distance to the aircraft. This reference point is used to create a tangent plane to then use the tangent plane as described herein as the basis for estimating the evolution of the aircraft's distance to the earth's surface, as far as the tangent plane is a sufficiently accurate map of the earth's surface (at least within the search angle range of the radar), that is, when the distance between the earth's surface and the tangent plane exceeds a predetermined distance value or deviation value at less than a predetermined number of points.

In addition, it should be noted that "encompassing" does not exclude other elements or steps, and "a" or "an" does not exclude a multitude. It should also be appreciated that features or steps described with reference to any of the above embodiments may also be used in combination with other features or steps of other embodiments described above. Reference signs in the claims are not to be considered as limiting.

LIST OF REFERENCE NUMBERS

10

mobile platform

15

radar lobe

20

reference surface

30

first value from

40

reference point

50

Connecting line between mobile platform and reference point

55

second distance value

60

vertical height

65

systematic error

70

tangent

80

deviation value

300

State determination unit

305

Inertial navigation system

310

radar

315

input matrix

320

Kalman filter

325

Totalizer, integrator

330

System dynamics matrix

335

Measuring matrix, control unit for radar

410

Arithmetic unit, processor

415

output

420

sensors

422

Position determining unit

424

Distance detection unit

430

data storage

Claims (12)

A method (500) for determining a state of a movable platform relative to a reference surface, the method comprising the steps of: Detecting (510) a first distance value (30) between the movable platform (10) and the reference surface (20); Determining (520) a second distance value (55) between the movable platform (10) and the reference surface (20) based on a model of the reference surface and a position of the movable platform relative to the reference surface, the second distance value (55) being the smallest distance between the reference surface and the movable platform; Determining (530) a difference between the first distance value (30) and the second distance value (55); Using (540) the difference as a residual and evaluating the residual to match a map of a state of the moveable platform to the state of the moveable platform. Method (500) Claim 1 , further comprising the step of: determining (550) a reference point (40) of the reference surface in the model of the reference surface based on the position of the movable platform relative to the model of the reference surface, the reference point of the movable platform being the smallest distance between the reference surface and the reference surface has movable platform. Method (500) Claim 2 , further comprising the step of: determining a tangent plane (70) which abuts the reference point (40) so that a connecting line (50) between the movable platform and the reference point perpendicularly intersects the tangent plane. Method (500) Claim 3 , further comprising the step of: comparing the tangent plane (70) to the model of the reference surface (20) in a predetermined region of the model of the reference surface. Method (500) Claim 4 , further comprising the step of: determining a respective deviation value (80) between the model of the reference surface (20) and the tangent plane (70) for each point of a plurality of predetermined points in the model of the reference surface. Method (500) Claim 5 method further comprising the steps of: determining the number of deviation values between the model of the reference surface and the tangent plane that exceed a predetermined deviation threshold; Discarding the detected first distance value if the number of deviation values exceeding the predetermined deviation threshold exceeds a predetermined threshold for that number. Method (500) according to one of the preceding claims, wherein said steps are performed in a repeating process as long as the movable platform is in motion. Method (500) according to one of the preceding claims, wherein the first distance value between the movable platform and the reference surface is detected by means of a radar system (424). Method (500) according to one of the preceding claims, wherein the movable platform (10) is an aircraft; wherein the reference surface (20) is the earth's surface; and where the model of the reference surface is a terrain database. A mobile platform state determination unit (300), the state determination unit comprising: a data memory (430) for holding a model of a reference surface; a position detecting unit (422) for detecting the position of the mobile platform with respect to a reference surface; a distance detecting unit (424) for detecting a distance of the mobile platform from the reference surface; wherein the state determination unit (300) is executed, the method according to one of Claims 1 to 9 perform. Mobile platform (10) with a state determination unit (300) according to Claim 10 , Mobile platform (10) after Claim 11 , wherein the mobile platform is an aircraft, a land vehicle or a watercraft.

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