Method of assisting navigation of a vehicle

Abstract

A method, navigation device and computer program product for assisting navigation of a vehicle equipped with a navigation device are provided, the method comprising the steps of: obtaining a prior value of a kinematic variable of the navigation device, determining (202) a respective current value of the kinematic variable of the navigation device and a current uncertainty matrix representing an uncertainty of the respective current value of the kinematic variable based on: a respective previous value of the kinematic variable, a previous uncertainty matrix representing an uncertainty of the respective previous value of the kinematic variable and a model of the earth's gravity experienced by the navigation device, the modelled gravity increasing with altitude of the navigation device.

Description

Technical Field

[0001] This invention relates to the field of methods for navigating vehicles, and more particularly to so-called hybrid navigation methods. Background Technology

[0002] Hybrid navigation methods are methods that fuse measurements from several sensors (accelerometers, gyroscopes, GPS, etc.) to determine kinematic variables or to determine the state of the device that implements the method.

[0003] These kinematic variables are, for example, the position, velocity, or orientation of the device.

[0004] Measurements are, for example, inertial measurements, such as those obtained from accelerometers and gyroscopes, like the specific force, angular rate, or rotational speed of a device; velocity measurements or position measurements of a device. Specific force is the sum of all external forces acting on a device other than gravity, divided by its mass. Therefore, this quantity has the dimension of acceleration.

[0005] In particular, using a conventional extended Kalman filter for high-level merging has limitations and requires a complex pre-alignment process.

[0006] As long as the uncertainty in heading and position is small enough, conventional extended Kalman filtering can work. This is particularly relevant to the alignment process at the start of navigation and, depending on the quality of the sensors used to obtain different measurements, more or less periodically resorting to additional measurements (in addition to altitude).

[0007] Furthermore, when the estimation error exceeds the uncertainty estimated by the Kalman filter, the instantaneous consistency loss cannot always be corrected by the filter due to the nonlinearity of the system. For example, this consistency loss can be caused by unpredictable increases in measurement noise.

[0008] While invariant filtering simplifies the alignment phase of the hybrid system, where it is theoretically applicable, it also has limitations in the case of inertial altimeter fusion. More precisely, the combination of invariant filtering with long-phase inertial altimeter fusion that intersects with rare position measurements does not provide any theoretical guarantee for the convergence of the filter. For inertial altimeter fusion, invariant filtering typically performs worse than conventional extended Kalman filters.

[0009] Therefore, a new navigation method is needed that can use altitude measurements in addition to other available measurements. Summary of the Invention

[0010] The present invention provides measures to remedy the above-mentioned shortcomings.

[0011] In this regard, according to a first aspect, the present invention provides a method for assisting navigation of a vehicle equipped with a navigation device, the method comprising the steps of: obtaining prior values ​​of kinematic variables of the navigation device; determining corresponding current values ​​of the kinematic variables of the navigation device and a current uncertainty matrix representing the uncertainty of the corresponding current values ​​of the kinematic variables based on: corresponding previous values ​​of the kinematic variables, a previous uncertainty matrix representing the uncertainty of the corresponding previous values ​​of the kinematic variables, and corresponding previous values ​​of a virtual Earth gravity model experienced by the navigation device, wherein the intensity of the modeled gravity increases with the height of the navigation device; determining corrections based on: the corresponding current values ​​and measured values ​​of the kinematic variables; and updating the corresponding current values ​​of the kinematic variables based on the corrections and the current uncertainty matrix.

[0012] Therefore, this method enables the determination of the values ​​of the kinematic variables of the navigation device. In particular, this method enables the control of the duration of the static initial phase (also known as alignment) at startup.

[0013] In one embodiment, the kinematic variables include: the orientation of the navigation device, the current value of which is a current orientation matrix, and the previous value of which is a previous orientation matrix; the velocity of the navigation device, the current value of which is a current velocity vector, and the previous value of which is a previous velocity vector; and the position of the navigation device, the current value of which is a current position vector, and the previous value of which is a previous position vector. The current uncertainty matrix represents the uncertainty of the current orientation matrix, the uncertainty of the current velocity vector, and the uncertainty of the current position vector; and the previous uncertainty matrix represents the uncertainty of the previous orientation matrix, the uncertainty of the previous velocity vector, and the uncertainty of the previous position vector.

[0014] In one embodiment, the current value is associated with the current time, and the previous value is associated with the previous time. Determining the current value of the kinematic variables includes: determining the current velocity vector by integrating the sum of the specific force of the navigation device and the modeled gravity over the time interval between the previous time and the current time into the previous velocity vector; determining the current position vector by integrating the previous velocity vector over the time interval into the previous position vector; determining the current orientation matrix by multiplying the previous orientation matrix by a matrix representing the rotation of the navigation device; or determining the current uncertainty matrix based on the previous uncertainty matrix.

[0015] In one embodiment, determining the correction involves subtracting the current velocity vector from the measured value and multiplying by the gain matrix.

[0016] In one embodiment, determining the correction involves subtracting the current position vector from the measured value and multiplying by the gain matrix.

[0017] In one embodiment, the correction is a correction vector, and the update includes the following sub-steps: updating the current orientation matrix by multiplying the rotation matrix of the first portion of the correction vector with the current orientation matrix; updating the current velocity vector by adding the product of the current rotation matrix and the second portion of the correction vector to the velocity vector; and updating the current position vector by adding the product of the current rotation matrix and the third portion of the correction vector to the current position vector.

[0018] In one embodiment, determining the kinematic variables of the navigation device includes the step of determining a virtual model of the experienced gravity using the following formula. in g n (X n ) is the modeled gravity vector. g réel A physically consistent model that is the opposite of Earth's gravitational modulus. r T For the radius of the Earth, X n The current position vector, and h n For measuring altitude of navigation devices.

[0019] In one embodiment, determining the kinematic variables of the navigation device includes the step of determining a virtual model of the experienced gravity using the following formula. Where g n (X n ) represents the modeled gravity vector, g réel Let r be the Earth's gravity vector from a physically consistent model. T Let X be the radius of the Earth. n h is the current position vector. n For measuring altitude of the navigation device, alt(X) n ) represents the altitude of the navigation device determined based on the current position vector, and This is the modified position vector where the height is the measured height.

[0020] Another aspect of the invention relates to a navigation device including a processing unit, three accelerometers, and three gyroscopes. The navigation device also includes a measuring device. The processing unit is configured to implement the previously described methods for assisting navigation.

[0021] In one embodiment, the navigation device further includes a measuring device for measuring the altitude of the navigation device.

[0022] Another aspect of the invention relates to a computer program product including program code instructions that, when executed by a processor, are used to perform the steps of the previously described method for assisted navigation. Attached Figure Description

[0023] Other features and advantages of the invention will become more apparent from the following description, which is purely illustrative and non-limiting, and must be read with reference to the accompanying drawings, in which:

[0024] Figure 1 The navigation system of the present invention is shown.

[0025] Figure 2 The navigation method of the present invention is illustrated.

[0026] Figure 3 A linear Kalman filter is shown.

[0027] Figure 4 An extended Kalman filter is shown. Detailed Implementation

[0028] Figure 1 A navigation device is schematically illustrated. This navigation device, a DISP (Dispositif de navigation), includes a processing unit (UNIT). The UNIT includes a processor or microcontroller for general or specific purposes, as well as memory.

[0029] The processor or microcontroller can be an application-specific integrated circuit (ASIC). Alternatively, it can be a field-programmable gate array (FPGA).

[0030] The memory can be fixed or removable and includes different memory cells, which may include combinations of cells that allow volatile and non-volatile storage. The memory is configured to store software code that can be used by a processor or microcontroller to embody a method for determining the corresponding values ​​of the kinematic variables of the navigation device's DISP.

[0031] The values ​​of the kinematic variables are used to locate the navigation device DISP, and thus to locate the navigation of the device's carrier.

[0032] The navigation device DISP also includes: Three accelerometers, 101-a to 101-c, Three gyroscopes, 102-a to 102-c, and A measuring device for measuring, for example, a physical quantity, based on one or more kinematic variables or on the deviation of one of the accelerometers or one of the gyroscopes. This measuring device is, for example, a measuring device 103-a for measuring the position of the navigation device DISP and / or a measuring device 103-b for measuring the velocity of the navigation device DISP.

[0033] The navigation device DISP may also include other devices for measuring the kinematic variables of the navigation device DISP.

[0034] In addition, the navigation device DISP may also include a measuring device 104 for measuring the height of the navigation device DISP. The measuring device 104 is, for example, an altimeter 104.

[0035] Three accelerometers, 101-a to 101-c, are capable of transmitting specific force data. Each of the three accelerometers is associated with a mutually orthogonal axis.

[0036] Three gyroscopes, 102-a to 102-c, are capable of transmitting angular position data. Each of the three gyroscopes is associated with one of three mutually orthogonal axes.

[0037] More precisely, the accelerometer measures the specific force f of the navigation device's DISP. n The gyroscope measures the angular velocity of the navigation device's DISP. This angular velocity is then converted into a rotation matrix Ω representing the rotation of the navigation device. n The time interval between two measurements is denoted as dt.

[0038] Accelerometers and gyroscopes can provide specific force and angular velocity, or directly provide changes in velocity and angle.

[0039] The measuring device 103-a for measuring the position of a navigation device DISP includes the following components: Satellite navigation receivers, such as GPS or Galileo receivers used for the Global Positioning System. A device that performs triangulation using vertices at known locations, or LiDAR (or LiDAR) device.

[0040] The measuring device 103-b for measuring the speed of the navigation device DISP is, for example, the following device: Devices using odometers, The device used to measure ship speed is also called a log, or The device used to detect when a vehicle has stopped is also called zupt (Zero velocity UPdaTe).

[0041] The processing unit receives the following data: data transmitted by three accelerometers 101-a to 101-c, data transmitted by three gyroscopes 102-a to 102-c, data transmitted by a measuring device 103-a for measuring position or by a measuring device 103-b for measuring velocity, and, where applicable, data transmitted by an altimeter 104.

[0042] If altimeter 104 is not present, an assumption can be made about the altitude of the navigation device DISP. If the carrier is a ship, an assumption can be made that the altitude is zero.

[0043] By implementing Figure 2 The method shown is for configuring the processing unit UNIT to determine the corresponding values ​​of the kinematic variables of the navigation device DISP. Therefore, this method enables the positioning of the navigation device DISP, and thus enables navigation of the device's carrier.

[0044] Figure 2 This method includes the following steps: Step 201: Obtain the prior kinematic variables of the navigation device; Step 202, determine the corresponding current values ​​of the kinematic variables of the navigation device DISP and the current uncertainty matrix representing the uncertainty of the corresponding current values ​​of the kinematic variables based on the following: the corresponding previous values ​​of the kinematic variables of the device DISP; the virtual Earth gravity model experienced by the device DISP, wherein the strength of the modeled gravity increases with the altitude of the device DISP; and the previous uncertainty matrix representing the uncertainty of the corresponding previous values ​​of the kinematic variables. Step 203, determine the correction based on the current values ​​of the kinematic variables and the measured values, and Step 204: Update or correct the current values ​​of the kinematic variables and the current uncertainty matrix based on the correction.

[0045] In this paper, the virtual model will be referred to interchangeably as the "virtual Earth gravity model" and the "virtual Earth gravitational model". The model does have fictional properties because the strength of the modeled gravity increases with the height of the DISP device, which is the opposite of the actual gravity / Earth gravity model, in which the strength of the modeled gravity decreases with the height of the DISP device.

[0046] The measured value is, for example, a physical quantity that is determined, for example, by one or more kinematic variables or by the deviation of one of the accelerometers or one of the gyroscopes. The measured value is, for example, the position or velocity of a navigation device's DISP.

[0047] Furthermore, the modeled gravity is consistent with the actual gravity at the measured height of the carrier.

[0048] The kinematic variables of the device include: The orientation of the device, the value of which is the current orientation matrix or the previous orientation matrix T, is a 3x3 matrix, and the orientation is represented by quaternions. The speed of the device, the value of which is the current velocity vector or the previous velocity vector, has a magnitude of 3, and The position of the device, the value of which is the current position vector or the previous position vector X, with a size of 3.

[0049] It can simultaneously estimate other variables, especially the deviations of accelerometer measurements and gyroscope measurements.

[0050] Furthermore, an uncertainty matrix P is used to represent the uncertainty of the kinematic variables. This matrix is ​​the covariance matrix.

[0051] In the remainder of this document, variables (matrices or vectors) marked with an accent circonflexe represent estimated variables; the corresponding actual variables are written without an accent circonflexe.

[0052] The method includes determining the values ​​of these variables, which are respectively represented as and The method also includes determining the covariance matrix P representing the uncertainty of the current estimate. n|n It is also assumed that the covariance matrix P represents the initial uncertainty. 0|0 It is available at the start of navigation.

[0053] Here, index n represents the time increment. Typically, in a Kalman filter, index n|n represents the estimate of the value at time n considering the observations made at time n, while index n|n-1 represents the estimate of the value at time n without considering the observations made at time n.

[0054] The method of the present invention uses a Kalman filter (advantageously, the present invention uses an invariant Kalman filter), which involves a continuous propagation phase (including determination 202) using inertial measurements and a virtual model of Earth's gravity, and an update phase (including determination 203 and correction 204) using position data transmitted by device 103-a for measuring position or velocity data transmitted by device 103-b for measuring velocity. In other embodiments, other types of measurements are used to determine correction 203 and perform update 204. Furthermore, during the determination phase 202, the method uses altitude measurements to feed a non-physical gravity model.

[0055] For example, in the case of an aircraft with a variable altitude and a navigation system, if an altimeter 104 is present, the altimeter 104 can provide the altitude measurement. In the case of a ship, the altitude measurement can also be known prior to the data.

[0056] 202 is determined using the following equation: in The current velocity vector, For the previous velocity vector, The current position vector, For the previous position vector, For the current orientation matrix, For the previously oriented matrix, A virtual model of the increased gravitational intensity experienced by the navigation device DISP. g réel This is a physically consistent model, the opposite of the gravitational modulus. The term "physically consistent" should be understood as a model in which the intensity of gravity is only a function of the distance from a point to the Earth's center, and that the intensity of gravity decreases with altitude. Therefore, in this virtual model, the following approximation is made: gravity is oriented towards the Earth's center and its modulus is only a function of the distance to the Earth's center. Q n Let Q be the covariance matrix, representing the increase in uncertainty at each step of the propagation of the kinematic variables. The primary source of this uncertainty is the inaccuracy of measurements from the accelerometer and gyroscope. To assign Q... n The exact value is often difficult to choose, but it can be selected using the specifications provided by the navigation device DISP manufacturer. r T This is the radius of the Earth (the distance to the Earth's center, which corresponds to zero altitude). h n The height of the device DISP. (l) × The antisymmetric matrix corresponding to the components of vector l is such that for any vector u, the following holds true: (l)× u=l×u Where × represents the vector product. P is the covariance matrix, where the values ​​on the diagonal represent the uncertainty of each state variable, and the values ​​off the diagonal represent the cross-uncertainty between kinematic variables. P n-1|n-1 For the previous uncertainty matrix, P n|n-1 This represents the current uncertainty matrix.

[0057] Therefore, in this determination step 202, a virtual Earth gravity model is used: g n (X n )=α n X n in

[0058] This virtual model is based on the actual model, but deviates from it. This virtual model uses g... réel g réel In contrast to the actual spherical model, in which the intensity of gravity is only a function of the distance from a point to the Earth's center, point X... n The true gravity at that location is written as: in To point to X n The unit vector in the direction of .

[0059] In addition, a virtual model g is used to apply gravity. n (X n )=α n X n The intensity of this gravity increases with altitude, but only at altitude h (indicated by the altimeter). n The result is consistent with the actual model.

[0060] Therefore, if position X n Located at height h n It gives: ||X n ||=r T +h n

[0061] And therefore, These two gravity models at height h n The two locations overlap.

[0062] But because of g n (X n ) becomes linear, so gn (X n (relative to X) n The derivative of gravity differs from that of gravity in a conventional model. This is no longer the case if a realistic, more complex gravity model is chosen. However, the filter performance remains the same.

[0063] You can also choose a more complex virtual Earth gravity model, such as using the following formula: Where the function g′ réel This is the Earth's gravity vector obtained from the physically consistent model. r t For the Earth The local radius of curvature. Let X be the latitude and longitude respectively. n The point with latitude and longitude, and an altitude of h. n . alt(X n ) is X n The height.

[0064] In one embodiment, step 203 of determining the correction ds includes: Subtract the current position vector from the position measurement of the navigation device (DISP). Where applicable, the difference obtained from the above subtraction is transformed into the carrier's reference frame using the estimated orientation matrix, and Multiply by the gain matrix.

[0065] More precisely, step 203 of determining the correction ds can be expressed using the following equation: ds = K n z n Where ds represents the correction. Y n The position is provided by the device used to measure position 103-a. R n Let be the covariance matrix used to represent measurement error and unmodeled quantities. It may or may not depend on the estimated kinematic variables. H n =(03 03 I3) This matrix can measure the position Y n Related to other kinematic variables of the device DISP, K nThis is either a gain matrix or a matrix that converts the error of the position vector into a matrix to correct for other kinematic variables.

[0066] If the measuring device provides a speed, then step 203 of determining the calibration ds performs the following operations: Subtract the current velocity vector from the velocity measured by the navigation device (DISP). Where applicable, the difference obtained from the above subtraction is transformed into the carrier's reference frame using the estimated orientation matrix, and Multiply by the gain matrix.

[0067] Therefore, if the measuring device provides velocity, then z n and H n The calculation is replaced by: H n =(03 I3 03) ds is a vector of size 9. The first three components (ds) 1:3 This corresponds to the rotational error. The next three components (ds) 4:6 ) corresponds to the velocity error. The last three components (ds 7:9 This corresponds to the position error.

[0068] Matrix H consists of a concatenation of two 3×3 zero matrices and a 3×3 identity matrix.

[0069] K is called the gain matrix.

[0070] The step 203 of determining the correction enables the determination of the deviation of all kinematic variables of the navigation device based solely on the value of one of the kinematic variables of the navigation device.

[0071] The determination of this deviation is performed by the gain matrix K, which takes into account the uncertainty of the kinematic variables of the device DISP. Under conditions of low uncertainty, the position measurement Y... n The degree of consideration is low, and under conditions of high uncertainty, the position measurement value Y n The degree of consideration is relatively high. The term "for position measurement value Y" is used. n "lower consideration" should be understood as referring to lower values ​​of elements in matrix K. The term "for position measurement value Y" should be understood as... n "The degree of consideration is relatively high" should be understood as meaning that the values ​​of the elements in matrix K are relatively high.

[0072] Update 204 uses the corrected ds to perform the following equation: P n|n =(IK n H n )P n|n-1 R is a function that allows us to obtain the rotation matrix of a vector based on that vector. ds 1:3 It is part of the correction vector related to orientation correction. ds 4:6 It is part of the correction vector related to velocity correction. ds 7:9 It is part of the correction vector related to position correction. It is the corrected velocity vector. It is the corrected position vector. It is the corrected orientation matrix. P n|n It is the corrected uncertainty matrix.

[0073] In another embodiment, update 204 uses the correction ds to perform the following equation: P n|n =(IK n H n )P n|n-1 in In other words, matrix V(ds) was inserted. 1:3 ).

[0074] Repeat steps 202 to 204 of this method throughout the navigation process.

[0075] Specifically, the corrected velocity vector Become the next previous velocity vector, the corrected position vector Become the next previous position vector, and the corrected orientation matrix. It becomes the next previously oriented matrix.

[0076] This method uses a matrix P as the covariance matrix, and applies a set of operations to P as it changes over time, known as the "Riccati equations". In the above embodiment, the kinematic variables never appear in matrix P (or only appear in matrix Q). n and R n(In the middle). Therefore, this method possesses an important property of linear systems. In more complex embodiments, these kinematic variables may arise, but the method of the present invention makes it possible to reduce the negative impact of this dependence.

[0077] In the preceding embodiments, the fusion technique used with the virtual Earth gravity model was an invariant filter. In other embodiments, other recalibration methods may be used, such as: A conventional extended Kalman filter; Smooth sliding window operation; Constant gain filter; Particle filter.

[0078] Figure 3 A linear Kalman filter is shown. The middle row shows the estimated kinematic variables after a series of propagations (using measurements from accelerometers and gyroscopes) and updates (using additional sensors, such as devices for measuring velocity or position). This update is a correction to the estimated state, taking into account the new measurements from the additional sensors. These sensors do not directly provide the correction to be made, but only the measured values. The difference between this measured value and the expected measured value is called innovation. To translate this innovation into a correction to the system state, a gain matrix K is necessary. The gain matrix K is calculated according to the Riccati equation in the bottom row. This equation updates the covariance matrix P, which represents the uncertainty of the kinematic variables. This covariance matrix P is used to construct the gain matrix K. If the estimate of the state is incorrect, the estimated value is corrected over time using the measurements combined with the gain matrix.

[0079] Figure 4 A nonlinear or extended Kalman filter is shown. This Kalman filter enables the management of the nonlinear aspects of the navigation device's state. Figure 4 and Figure 3 The difference lies in adding the feedback from the middle row to the bottom row. Therefore, in this filter, the estimated state is used to calculate the uncertainty and gain. This feedback can degrade the filter's performance. Errors in the system state introduce errors in the gain, which in turn introduce errors in the estimated state.

[0080] In one implementation of the present invention, a set of operations involving matrix P does not cause estimation errors in the navigation device DISP (or ensures that the estimation error of the navigation device DISP only occurs in matrix Q). n and R n (in Chinese). Therefore, the present invention is in the same situation as a linear system. Figure 4 The impact of the feedback is gone.

Claims

1. A method for assisting navigation in a vehicle equipped with a navigation device, the method comprising the following steps: Obtain the prior values ​​of the kinematic variables of the navigation device and the measured altitude of the navigation device. The kinematic variables include: The navigation device's orientation, where the current value of the orientation is the current orientation matrix, and the previous value of the orientation is the previous orientation matrix. The speed of the navigation device, the current value of the speed is the current speed vector, the previous value of the speed is the previous speed vector, and The position of the navigation device, wherein the current value of the position is the current position vector, and the previous value of the position is the previous position vector; Using a Kalman filter, the updated values ​​of the kinematic variables are determined. , , ),include: Determine the vector model of the gravity experienced by the navigation device. The intensity of the modeled gravity varies with the measured altitude of the navigation device. The vector increases with the formula. To determine, among which , in, A physically consistent model that is the opposite of Earth's gravitational modulus. The radius of the Earth, the measured altitude of the navigation device Defined as making ; The current values ​​of the kinematic variables of the navigation device are determined based on the following: , , ): The corresponding previous values ​​of the kinematic variables ( , , ), A vector model of the Earth's gravity experienced by the navigation device. ; The current uncertainty matrix, representing the uncertainty of the corresponding current values ​​of the current orientation matrix, the current velocity vector, and the current position vector, is determined based on the following: : Previous uncertainty matrix This represents the uncertainty of the previous orientation matrix, the previous velocity vector, and the previous position vector, and Transition matrix Defined as ,in, The specific force of the navigation device, The transpose of the matrix representing the rotation of the navigation device; The correction is determined based on the following: : The corresponding current values ​​of the kinematic variables ( , , ), The current uncertainty matrix ,and Measured values ,as well as Based on the correction And the current uncertainty matrix, update the corresponding current values ​​of the kinematic variables ( , , And update the current uncertainty matrix. To obtain the updated value.

2. The method of claim 1, wherein the current value is associated with the current time, the previous value is associated with a previous time, and determining the current value of the kinematic variable and the current uncertainty matrix includes the following: The current velocity vector is determined by integrating the sum of the specific force of the navigation device and the vector modeled by the Earth's gravity experienced by the navigation device over the time interval between the previous time and the current time into the previous velocity vector; such that... ， By using the previous velocity vector The integral over the time interval is added to the previous position vector. Determine the current position vector ; make ， By using the previous orientation matrix Multiply by the matrix representing the rotation of the navigation device Determine the current orientation matrix , making .

3. The method according to claim 1 or 2, wherein determining the correction comprises: The current velocity vector and the measured value Subtract, and Multiply by the gain matrix.

4. The method according to claim 2, wherein determining the correction comprises: Subtract the current position vector from the measured value, and Multiply by the gain matrix.

5. The method according to claim 1 or 2, wherein the correction is a correction vector, and the update includes the following: The sub-step of updating the current orientation matrix by multiplying the current rotation matrix of the first part of the correction vector with the current orientation matrix; The sub-step of updating the current velocity vector by adding the product of the current rotation matrix and the second part of the correction vector to the current velocity vector; and The sub-step of updating the current position vector by adding the product of the current rotation matrix and the third part of the correction vector to the current position vector.

6. A navigation device for a vehicle, comprising: Processing unit Three accelerometers, and Three gyroscopes; The navigation device also includes: Measuring device; The processing unit is configured to implement the method for assisted navigation according to any one of claims 1 to 5.

7. The navigation device according to claim 6 further includes a measuring device for measuring the measurement altitude of the navigation device.

8. A computer program product comprising program code instructions, which, when executed by a processor, are configured to perform the steps of the method for assisted navigation according to any one of claims 1 to 5.

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