Multi-epoch associated dynamic inverse synthetic aperture radio positioning method

Abstract

The invention relates to a multi-epoch associated dynamic inverse synthetic aperture radio positioning method, and belongs to the technical field of signal processing, navigation positioning, spaceflight measurement and control and target tracking. The method specifically comprises the following steps of: 1, acquiring relative observed quantity h of N epoch anchor points and a moving target; 2, carrying out the fitting modeling of the time-varying position and speed of the moving target through the time-invariant trajectory parameters, and obtaining a moving target trajectory model; step 3, representing the time-varying position and speed of the moving target in the observed quantity h in the step 1 by using the moving target trajectory model, establishing and solving a positioning target function of each trajectory model, and obtaining a fitting coefficient in the moving target trajectory model; and reversely deducing the time-varying position and speed of the moving target based on the fitting coefficient to realize inverse synthetic aperture positioning.

Description

Technical Field

[0001] The invention relates to a multi-epoch-associated dynamic inverse synthetic aperture radio positioning method, belonging to the technical fields of signal processing, navigation positioning, aerospace measurement and control, and target tracking. Background Art

[0002] Radio navigation positioning, including satellite navigation, ground-based navigation, and cellular signal navigation, boasts all-weather, all-day operation, long range, and high positioning accuracy, making it widely used in numerous civil and military fields. In radio navigation positioning, an anchor point measures the relative distance, velocity, and angle to the target to be located, and solves equations to achieve positioning. The accuracy of angle measurement is generally related to the effective aperture size of the antenna. A larger antenna aperture increases the angle measurement accuracy, and the calculated target position is more precise.

[0003] Conventional radio positioning methods use instantaneous distance and angle measurements from anchor points to locate the target. For a single anchor point, if the antenna aperture is limited, the instantaneous angle measurement will contain large errors, degrading positioning accuracy. Furthermore, the greater the relative distance between the target and the anchor point, the greater the positioning deviation will be due to the same angle measurement error. Therefore, conventional positioning methods using instantaneous observations have limited accuracy in scenarios with small antenna apertures or long ranges. Summary of the Invention

[0004] The purpose of the present invention is to provide a multi-epoch-associated dynamic inverse synthetic aperture radio positioning method, which can improve positioning accuracy when the observed quantity has a large measurement error.

[0005] The technical solutions for implementing the present invention are as follows:

[0006] In a first aspect, the present invention provides a multi-epoch-associated dynamic inverse synthetic aperture radio positioning method, the specific process of which is as follows:

[0007] Step 1: Obtain the relative observation h between the N epoch anchor points and the moving target;

[0008] Step 2: Use the time-invariant trajectory parameters to fit the time-varying position and velocity of the moving target to obtain the moving target trajectory model;

[0009] Step three, the time-varying position and velocity of the moving target in the observation quantity h in step one are represented by the moving target trajectory model, and the positioning target function of each trajectory model is established and solved to obtain the fitting coefficients in the moving target trajectory model; based on the fitting coefficients, the time-varying position and velocity of the moving target are inferred to achieve inverse synthetic aperture positioning.

[0010] Optionally, the present invention uses time-invariant trajectory parameters to fit the time-varying position and velocity of the moving target as follows:

[0011]

[0012] Among them, α l , β l are the initial epoch position, velocity fitting polynomial coefficients, and the instantaneous invariant trajectory parameters, ξ l,t is the orthogonal polynomial basis, and L is the order of the fitting coefficient.

[0013] Optionally, in step 3 of the present invention, the time-varying position and velocity of the moving target in the observation h in step 1 are represented by the moving target trajectory model, specifically:

[0014]

[0015] Among them, ρ i,t 、f i,t , α i,t as well as They represent the relative distance, velocity, azimuth and elevation angle observations between the anchor point i and the moving target at epoch t, Respectively The x, y, and z axis components of represents the three-dimensional position of the i-th stationary anchor point, arctan() represents the inverse tangent operation, n ρ 、n f 、n α 、 They represent the measurement errors of distance, speed, azimuth and elevation respectively.

[0016] Optionally, the objective function of the present invention is:

[0017]

[0018] Among them, f({α,β} L ) represents the mapping function between the position and velocity fitting polynomial coefficients and the relative observation h, and W is the covariance matrix of the distance, velocity, azimuth and elevation observation noise.

[0019] Optionally, the objective function of the present invention is solved by the Gauss-Newton iterative method to obtain the time invariant {α, β} L =[α1...,α L ,β1...,β L ].

[0020] In a second aspect, the present invention provides a multi-epoch-associated dynamic inverse synthetic aperture radio positioning device, comprising:

[0021] The observation acquisition module is used to obtain the relative observation h between N epoch anchor points and the moving target;

[0022] The target trajectory fitting module uses the time-invariant trajectory parameters to fit the time-varying position and velocity of the moving target to obtain the moving target trajectory model;

[0023] The synthetic aperture positioning module is used to represent the time-varying position and velocity of the moving target in the observation quantity h using the moving target trajectory model, establish and solve the positioning target function of each trajectory model, and obtain the fitting coefficients in the moving target trajectory model; based on the fitting coefficients, the time-varying position and velocity of the moving target are inferred to achieve inverse synthetic aperture positioning.

[0024] Beneficial effects:

[0025] The present invention regards the position change of the moving target at different moments as a "virtual baseline", compensates for the target position change by modeling the moving target trajectory through a time-invariant polynomial, and coherently synthesizes the distance, speed and angle observations between the anchor point and the moving target at different moments. The coherent synthesis of multiple instantaneous observations produces an "effective aperture" that is much larger than a single observation, thereby reducing the observation error and improving the positioning accuracy of the moving target. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0027] Figure 1 It is a flow chart of the structure of the method of the present invention. DETAILED DESCRIPTION

[0028] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0029] It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments may be combined with each other; and, based on the embodiments in this disclosure, all other embodiments obtained by those of ordinary skill in the art without creative work are within the scope of protection of this disclosure.

[0030] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on this disclosure, it should be understood by those skilled in the art that an aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects described herein can be used to implement an apparatus and / or practice a method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement this apparatus and / or practice this method.

[0031] The structural diagram of the present invention is as follows Figure 1 As shown, the embodiment of the present application includes three steps: extracting and merging multi-epoch observations, modeling the trajectory of the moving target, and establishing and solving the positioning target function. Figure 1 shown.

[0032] Step 1: Obtain the relative observation h between the N epoch anchor points and the moving target;

[0033] Step 2: Use the time-invariant trajectory parameters to fit the time-varying position and velocity of the moving target to obtain the moving target trajectory model;

[0034] Step three, the time-varying position and velocity of the moving target in the observation quantity h in step one are represented by the moving target trajectory model, and the positioning target function of each trajectory model is established and solved to obtain the fitting coefficients in the moving target trajectory model; based on the fitting coefficients, the time-varying position and velocity of the moving target are inferred to achieve inverse synthetic aperture positioning.

[0035] This embodiment combines the instantaneous distance, velocity, and angle observations of the anchor point and the moving target to be located from multiple epochs to coherently synthesize an "effective aperture" much larger than a single instantaneous observation to improve positioning accuracy. The specific process of each step is described in detail below:

[0036] (1) Extraction and merging of multi-epoch observations

[0037] Assume that the number of anchor points is M, for t epochs, D t The observation quantity h of anchor points and moving targets t It can be expressed as

[0038]

[0039] Among them, ρ i,t 、f i,t , α i,t as well as They represent the relative distance, velocity, azimuth and elevation angle observations (known quantities) between the anchor point i and the moving target at epoch t, respectively. They can be specifically expressed as

[0040] ρ i,t =||p t -s i ||+n ρ

[0041]

[0042] in, Represents the three-dimensional position of the moving target, () T represents the transpose operation, represents the 3D position of the i-th stationary anchor point, v t Indicates the three-dimensional velocity of the moving target, arctan() indicates the inverse tangent operation, n ρ 、n f 、n α 、 Respectively represent the measurement errors of distance, speed, azimuth and elevation. In formula (2), p t and v t is the unknown parameter to be solved.

[0043] The anchor point is used for inverse synthetic aperture positioning by combining the observations of N epochs. The combined observations can be combined and expressed as

[0044]

[0045] In a time period of length N, the number of observations in each epoch is 4D t The total number of observations obtained is

[0046] (2) Moving target trajectory modeling

[0047] Combining multi-epoch observations effectively increases the number of observations. Because the position of a moving target varies over time, combining multi-epoch observations will result in a proportional increase in the number of variables in the positioning solution. Therefore, it is necessary to fit the time-varying position using time-invariant trajectory parameters to correlate the unknowns in the multi-epoch solution, thereby compensating for the target position change and coherently combining the multi-epoch observations.

[0048] Considering that the trajectory of the moving target has a short-term stationary characteristic, the time-varying position and velocity of the moving target in a time period of length N are calculated using an orthogonal polynomial model h(α1,...,α L ,β1,...,β L ) is used for modeling, namely:

[0049]

[0050] Among them, α l , β l are the initial epoch position and velocity fitting polynomial coefficients, ξ l,t is an orthogonal polynomial basis function with respect to time.

[0051] Through the trajectory model, the time-varying position p of the moving target is t , time-varying velocity v t The time-invariant parameter α l , β l , l∈{1,...,L}. The number of trajectory model solution variables is only related to the variables to be determined in the initial epoch trajectory model, that is, multiple epochs share the same solution variables, thus achieving coherent synthesis of multi-epoch observations.

[0052] (3) Establishment and solution of positioning target function

[0053] After the trajectory of the moving target is modeled using the trajectory model, the multi-epoch observations are coherently synthesized, and the trajectory model parameters are constructed to solve the objective function for positioning. L ,β1,...,β L ) into the t epoch observation, the t epoch observation can be associated with the initial epoch trajectory model parameters:

[0054]

[0055] in, Respectively The x, y, and z axis components of .

[0056] Combining the above formulas, we can coherently synthesize the instantaneous observations of multiple epochs and establish the relationship between the unknowns {α, β} L =[α1...,α L ,β1...,β L ], expressed as:

[0057] h=f({α,β} L )+ε (7)

[0058] Among them, f({α,β} L ) represents the mapping function between the position and velocity fitting polynomial coefficients and the relative observation h, and ε represents the measurement noise

[0059] Thus, the positioning objective function can be constructed for each trajectory model:

[0060]

[0061] Where W is the covariance matrix of the distance, velocity, azimuth and elevation observation noise.

[0062] The objective function can be solved by the Gauss-Newton iteration method to obtain the trajectory model solution variables {α, β} L =[α1...,α L ,β1...,β L ], and further based on the model parameters, the time-varying position and velocity of the moving target are inferred to achieve inverse synthetic aperture positioning.

[0063] Another embodiment of the present application is a multi-epoch-correlated dynamic inverse synthetic aperture radio positioning device, comprising:

[0064] The observation acquisition module is used to obtain the relative observations between N epoch anchor points and the moving target;

[0065] The target trajectory fitting module uses the time-invariant trajectory parameters to fit the time-varying position and velocity of the moving target to obtain the moving target trajectory model;

[0066] The synthetic aperture positioning module is used to represent the time-varying position and velocity of the moving target in the observation quantity using the moving target trajectory model, establish and solve the positioning target function of each trajectory model, and obtain the fitting coefficients in the moving target trajectory model; based on the fitting coefficients, the time-varying position and velocity of the moving target are inferred to achieve inverse synthetic aperture positioning.

[0067] The anchor point of the present invention obtains the distance, speed and angle observations from the moving target at different times, regards the position change of the moving target at different times as a "virtual baseline", models the trajectory of the moving target through a time-invariant polynomial, and compensates for the target position change. Multiple instantaneous observations are coherently synthesized to produce an "effective aperture" that is much larger than a single observation, thereby improving the angle measurement resolution and the positioning accuracy of the moving target.

[0068] In summary, the above are only preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A multi-epoch-correlated dynamic inverse synthetic aperture radio positioning method, characterized in that: The specific process is: Step 1: Obtain the relative observation h between the N epoch anchor points and the moving target; Step 2: Use the time-invariant trajectory parameters to fit the time-varying position and velocity of the moving target to obtain the moving target trajectory model; Step three, the time-varying position and velocity of the moving target in the observation quantity h in step one are represented by the moving target trajectory model, and the positioning target function of each trajectory model is established and solved to obtain the fitting coefficients in the moving target trajectory model; based on the fitting coefficients, the time-varying position and velocity of the moving target are inferred to achieve inverse synthetic aperture positioning.

2. The multi-epoch-associated dynamic inverse synthetic aperture radio positioning method according to claim 1, wherein: The time-varying position and velocity fitting model of the moving target using time-invariant trajectory parameters is: Among them, α l , β l are the initial epoch position and velocity fitting polynomial coefficients, ξ l,t is the orthogonal polynomial basis, and L is the order of the fitting coefficient.

3. The multi-epoch-associated dynamic inverse synthetic aperture radio positioning method according to claim 2, wherein: In step 3, the time-varying position and velocity of the moving target in the observation h in step 1 are represented by the moving target trajectory model, specifically: Among them, ρ i,t 、f i,t , α i,t as well as They represent the relative distance, velocity, azimuth and elevation angle observations between the anchor point i and the moving target at epoch t, Respectively The x, y, and z axis components of represents the three-dimensional position of the i-th stationary anchor point, arctan() represents the inverse tangent operation, n ρ 、n f 、n α 、 They represent the measurement errors of distance, speed, azimuth and elevation respectively.

4. The multi-epoch-associated dynamic inverse synthetic aperture radio positioning method according to claim 3, wherein: The objective function is: Among them, f({α,β} L ) represents the mapping function between the position and velocity fitting polynomial coefficients and the relative observation h, and W is the covariance matrix of the distance, velocity, azimuth and elevation observation noise.

5. The multi-epoch-associated dynamic inverse synthetic aperture radio positioning method according to claim 4, characterized in that: The objective function is solved by the Gauss-Newton iteration method to obtain the time invariant {α, β} L =[α1...,α L ,β1...,β L ].

6. A multi-epoch-associated dynamic inverse synthetic aperture radio positioning device, characterized in that: include: The observation acquisition module is used to obtain the relative observation h between N epoch anchor points and the moving target; The target trajectory fitting module uses the time-invariant trajectory parameters to fit the time-varying position and velocity of the moving target to obtain the moving target trajectory model; The synthetic aperture positioning module is used to represent the time-varying position and velocity of the moving target in the observation quantity h using the moving target trajectory model, establish and solve the positioning target function of each trajectory model, and obtain the fitting coefficients in the moving target trajectory model; based on the fitting coefficients, the time-varying position and velocity of the moving target are inferred to achieve inverse synthetic aperture positioning.

7. The multi-epoch-associated dynamic inverse synthetic aperture radio positioning device according to claim 6, characterized in that: The time-varying position and velocity fitting model of the moving target using time-invariant trajectory parameters is: Among them, α l , β l are the initial epoch position and velocity fitting polynomial coefficients, ξ l,t is the orthogonal polynomial basis, and L is the order of the fitting coefficient.

8. The multi-epoch-associated dynamic inverse synthetic aperture radio positioning device according to claim 7, characterized in that: The time-varying position and velocity of the moving target in the observation h are represented by the moving target trajectory model, specifically: Among them, ρ i,t 、f i,t , α i,t as well as They represent the relative distance, velocity, azimuth and elevation angle observations between the anchor point i and the moving target at epoch t, Respectively The x, y, and z axis components of represents the three-dimensional position of the i-th stationary anchor point, arctan() represents the inverse tangent operation, n ρ 、n f 、n α 、 They represent the measurement errors of distance, speed, azimuth and elevation respectively.

9. The multi-epoch-associated dynamic inverse synthetic aperture radio positioning method according to claim 8, characterized in that: The objective function is: Among them, f({α,β} L ) represents the mapping function between the position and velocity fitting polynomial coefficients and the relative observation h, and W is the covariance matrix of the distance, velocity, azimuth and elevation observation noise.

10. The multi-epoch-associated dynamic inverse synthetic aperture radio positioning method according to claim 9, characterized in that: The objective function is solved by the Gauss-Newton iteration method to obtain the time invariant {α, β} L =[α1...,α L ,β1...,β L ].

Images