High-speed rendezvous target trajectory parameter estimation method and device, electronic equipment and medium

Abstract

The application provides a high-speed rendezvous target trajectory parameter estimation method and device, electronic equipment and storage medium, through receiving echo signals reflected by a target; sampling the echo signals to obtain multi-channel baseband signals; inputting the multi-channel baseband signals into a scalar miss distance estimator and a vector miss distance estimator; determining a high-speed rendezvous target trajectory parameter estimation result according to output results of the scalar miss distance estimator and the vector miss distance estimator, so that higher measurement accuracy can be obtained on the basis that the calculation amount is far less than that of a traditional direct positioning method, thereby making the high-speed rendezvous target trajectory parameter estimation more efficient, and the estimation result is more accurate compared with a traditional fast estimation method.

Description

Technical Field

[0001] This invention relates to the field of target trajectory parameter estimation technology, and in particular to a method, apparatus, electronic device, and storage medium for estimating the trajectory parameters of a high-speed rendezvous target. Background Technology

[0002] With the development of modern warfare, precision strike capability has become an important direction for weapon system development. Traditionally, weapon strike accuracy was assessed through multiple tests for evaluation and acceptance. However, due to a lack of testing conditions, this method has gradually been replaced by miss distance measurement techniques under small sample conditions. Currently, common miss distance measurement methods involve installing various measuring instruments near the target and analyzing the target's terminal trajectory to obtain the weapon system's strike accuracy. Among these methods, miss distance measurement based on active radar has gradually emerged as a superior approach compared to acoustic, electrostatic, and optical methods due to its independence from weather and optical limitations, and is gaining increasingly widespread application.

[0003] In current scenarios for measuring short-range, high-speed rendezvous target parameters using Doppler radar, echo data from targets near the miss point is difficult to detect and process due to its low-frequency and non-stationary characteristics, and is often discarded. However, the non-stationary nature of the echo data near the miss point precisely reflects the rapidly changing positional relationship between the target and the radar, making it crucial for achieving high-precision target trajectory measurement. Common methods for measuring miss distance near the miss point include the two-step method and the direct positioning method. The two-step method requires estimating intermediate parameters of the target's motion, such as arrival time, arrival angle, and Doppler frequency, and then using a fitting method to obtain the target's motion parameters. Because the two-step method has poor performance in estimating intermediate parameters for strong non-stationary signals, and the estimation error of these intermediate parameters directly affects the trajectory parameter estimation in the second step, it is difficult to achieve particularly high measurement accuracy. While the direct positioning method does not have the problem of intermediate parameter estimation, target trajectory positioning in three-dimensional space requires at least six-dimensional optimization of its trajectory parameters, which often involves a large computational load and is prone to getting trapped in local optima, leading to inaccurate measurement results. Summary of the Invention

[0004] This invention provides a method, apparatus, electronic device, and storage medium for estimating trajectory parameters of a high-speed rendezvous target, which solves the problem of low measurement accuracy caused by estimation errors of intermediate parameters in traditional high-speed rendezvous target trajectory parameter estimation methods, as well as the defects of inaccurate measurement results caused by large computational load and easy getting trapped in local optima when performing six-dimensional optimization of trajectory parameters.

[0005] This invention provides a method for estimating trajectory parameters of a high-speed rendezvous target, comprising:

[0006] Receive the echo signal after it has been reflected from the target;

[0007] The echo signal is sampled to obtain a multi-channel baseband signal;

[0008] The multi-channel baseband signal is input into the scalar miss estimate and the vector miss estimate;

[0009] The trajectory parameter estimation results of the high-speed rendezvous target are determined based on the output results of the scalar miss estimate and the vector miss estimate.

[0010] According to a high-speed rendezvous target trajectory parameter estimation method provided by the present invention, the scalar miss distance estimator acquisition method includes:

[0011] The complex amplitude and phase of the signal in a single channel can be analyzed from the baseband signal of that channel.

[0012] Calculate the maximum likelihood estimate of the complex amplitude of the signal in this channel;

[0013] The joint probability density of the echo signal in the channel as a function of the scalar miss distance is obtained based on the maximum likelihood estimate of the complex amplitude of the signal in the channel and the phase of the signal in the channel.

[0014] A scalar miss estimate is obtained based on the joint probability density of the echo signals in the channel as a function of the scalar miss amount.

[0015] According to the present invention, a method for estimating trajectory parameters of a high-speed rendezvous target is provided, wherein the method for obtaining the vector miss distance estimator includes:

[0016] Geometric constraints are set based on the spatial location of the target at each sampling moment during the rendezvous process, obtained from multi-channel baseband signals.

[0017] The joint probability density of the echo signal in each channel is calculated as a function of the vector miss distance based on the maximum likelihood estimate of the complex amplitude of the signal in each channel and the phase of the signal in each channel.

[0018] A vector miss distance estimator is obtained based on the geometric constraints and the joint probability density of the echo signals in each channel.

[0019] According to the present invention, a method for estimating trajectory parameters of a high-speed rendezvous target is provided, wherein the method for obtaining the vector miss distance estimator includes:

[0020] Obtain the inherent phase difference between different receiving channels, and compensate for the complex amplitude of the echo signal of each receiving channel based on the inherent phase difference between different receiving channels;

[0021] Calculate the maximum likelihood estimate of the complex amplitude of the echo signal after compensation;

[0022] The corrected joint probability density of the echo signal in each channel is calculated based on the maximum likelihood estimate of the complex amplitude of the compensated echo signal and the phase of the signal in each channel.

[0023] Geometric constraints are set based on the spatial location of the target at each sampling moment during the rendezvous process, obtained from multi-channel baseband signals.

[0024] A vector miss distance estimator is obtained based on the geometric constraints and the modified joint probability density of the echo signal in each channel.

[0025] The method for estimating trajectory parameters of a high-speed rendezvous target provided by the present invention further includes:

[0026] If a set of miss parameters corresponds to multiple sets of trajectory parameters, then the trajectory parameter with the largest output modified joint probability density function value is selected as the optimal modified joint probability density function.

[0027] The vector miss estimate is obtained based on the optimal modified joint probability density function.

[0028] According to the present invention, a method for estimating the trajectory parameters of a high-speed rendezvous target is provided, wherein determining the trajectory parameter estimation result of the high-speed rendezvous target based on the output results of the scalar miss distance estimator and the vector miss distance estimator includes:

[0029] The possible range of target trajectory parameters is divided into grids according to actual needs using the grid search method.

[0030] The cost function value corresponding to each grid is calculated, and the grid point corresponding to the maximum value of the cost function is selected as the parameter estimation result of the high-speed rendezvous target trajectory.

[0031] According to the present invention, a method for estimating trajectory parameters of a high-speed rendezvous target is provided, wherein the estimation result of the high-speed rendezvous target trajectory parameters includes:

[0032] Scalar miss distance parameters, vector miss distance parameters, and the target's miss point coordinates;

[0033] The scalar miss distance parameter includes the distance between the target's initial position and the miss point, the target's velocity, and the scalar miss distance.

[0034] The vector miss parameters include the ballistic deflection angle, the ballistic tilt angle, and the z-coordinate of the miss point in the measurement coordinate system.

[0035] The present invention also provides a high-speed rendezvous target trajectory parameter estimation device, comprising:

[0036] The receiving module is used to receive the echo signal after it has been reflected from the target.

[0037] The sampling module is used to sample the echo signal to obtain a multi-channel baseband signal;

[0038] The input module is used to input the multi-channel baseband signal into the scalar miss estimate and the vector miss estimate;

[0039] The output module is used to determine the trajectory parameter estimation results of the high-speed rendezvous target based on the output results of the scalar miss estimater and the vector miss estimater.

[0040] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the high-speed rendezvous target trajectory parameter estimation method described in any of the preceding claims.

[0041] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the high-speed rendezvous target trajectory parameter estimation method described in any of the preceding claims.

[0042] The high-speed rendezvous target trajectory parameter estimation method, apparatus, electronic device, and storage medium provided by this invention receive the echo signal after reflection from the target; sample the echo signal to obtain a multi-channel baseband signal; input the multi-channel baseband signal into a scalar miss distance estimator and a vector miss distance estimator; and determine the high-speed rendezvous target trajectory parameter estimation result based on the output results of the scalar miss distance estimator and the vector miss distance estimator. This method can achieve higher measurement accuracy with a computational load far less than the traditional direct positioning method, thus making the high-speed rendezvous target trajectory parameter estimation more efficient and the estimation result more accurate than the traditional fast estimation method. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0044] Figure 1 This is one of the flowcharts illustrating the high-speed rendezvous target trajectory parameter estimation method provided by the present invention;

[0045] Figure 2 This is the second flowchart illustrating the high-speed rendezvous target trajectory parameter estimation method provided by the present invention;

[0046] Figure 3 This is a schematic diagram of the measurement scenario provided by the present invention;

[0047] Figure 4 The third flowchart illustrating the high-speed rendezvous target trajectory parameter estimation method provided by this invention;

[0048] Figure 5 The fourth flowchart illustrating the high-speed rendezvous target trajectory parameter estimation method provided by this invention;

[0049] Figure 6 Fifth flowchart illustrating the high-speed rendezvous target trajectory parameter estimation method provided by the present invention;

[0050] Figure 7 A comparison of the root mean square error of the estimation results of the scalar off-target parameter r of simulation data with different signal-to-noise ratios provided by the method of this invention and other methods;

[0051] Figure 8 A comparison of the root mean square error of the method provided in this invention with other methods for estimating the target motion velocity v of simulation data with different signal-to-noise ratios;

[0052] Figure 9 A comparison of the root mean square error of the motion distance l estimation results of the method provided by this invention and other methods on simulation data with different signal-to-noise ratios;

[0053] Figure 10 A comparison of the root mean square error of the ballistic deflection angle α estimation results of the method provided by this invention and other methods for simulation data with different signal-to-noise ratios;

[0054] Figure 11 A comparison of the root mean square error of the ballistic inclination angle β estimation results of the method provided by this invention and other methods for simulation data with different signal-to-noise ratios;

[0055] Figure 12 A comparison of the root mean square error of the off-target x-coordinate estimation results of the method provided by this invention and other methods for simulation data with different signal-to-noise ratios;

[0056] Figure 13 A comparison of the root mean square error of the off-target y-coordinate estimation results of the method provided by this invention and other methods for simulation data with different signal-to-noise ratios;

[0057] Figure 14 A comparison of the root mean square error of the off-target z-coordinate estimation results of the method provided by this invention and other methods for simulation data with different signal-to-noise ratios;

[0058] Figure 15 This is a schematic diagram of the high-speed rendezvous target trajectory parameter estimation device provided by the present invention;

[0059] Figure 16 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0061] Figure 1 A flowchart of the high-speed rendezvous target trajectory parameter estimation method provided in the embodiments of the present invention is shown below. Figure 1 As shown, the high-speed rendezvous target trajectory parameter estimation method provided in this embodiment of the invention includes:

[0062] Step 101: Receive the echo signal after it has been reflected by the target;

[0063] Step 102: Sample the echo signal to obtain a multi-channel baseband signal;

[0064] Step 103: Input the multi-channel baseband signal into the scalar miss estimate and the vector miss estimate;

[0065] Step 104: Determine the trajectory parameter estimation results of the high-speed rendezvous target based on the output results of the scalar miss estimater and the vector miss estimater.

[0066] In this embodiment of the invention, the trajectory parameter estimation results of the high-speed rendezvous target include:

[0067] Scalar miss distance parameters, vector miss distance parameters, and the target's miss point coordinates;

[0068] The scalar miss distance parameter includes the distance between the target's initial position and the miss point, the target's velocity, and the scalar miss distance.

[0069] The vector miss parameters include the ballistic deflection angle, the ballistic inclination angle, and the z-coordinate of the miss point in the measurement coordinate system.

[0070] Traditional methods for measuring miss distance when a target passes near the miss point commonly include the two-step method and the direct positioning method. The two-step method requires estimating intermediate parameters of the target's motion, such as arrival time, arrival angle, and Doppler frequency, and then using a fitting method to obtain the target's motion parameters. Because the two-step method performs poorly in estimating intermediate parameters for strong non-stationary signals, and the estimation error of these intermediate parameters directly affects the trajectory parameter estimation in the second step, it is difficult to achieve particularly high measurement accuracy. While the direct positioning method does not have the problem of intermediate parameter estimation, the target trajectory positioning in three-dimensional space requires at least six-dimensional optimization of its trajectory parameters. This often involves a large computational load and is prone to getting trapped in local optima, leading to inaccurate measurement results.

[0071] The high-speed rendezvous target trajectory parameter estimation method provided in this invention receives the echo signal after reflection from the target; samples the echo signal to obtain a multi-channel baseband signal; inputs the multi-channel baseband signal into a scalar miss distance estimator and a vector miss distance estimator; and determines the high-speed rendezvous target trajectory parameter estimation result based on the output results of the scalar miss distance estimator and the vector miss distance estimator. This method can achieve higher measurement accuracy with a computational load far less than the traditional direct positioning method, thus making the high-speed rendezvous target trajectory parameter estimation more efficient and the estimation result more accurate.

[0072] Based on any of the above embodiments, such as Figure 2 As shown, the method for obtaining the scalar miss estimate includes:

[0073] Step 201: Analyze the complex amplitude and phase of the signal in a single channel based on the baseband signal of that channel;

[0074] Step 202: Calculate the joint probability density of the echo signal in the channel based on the maximum likelihood estimate of the complex amplitude of the signal in the channel and the phase of the signal in the channel;

[0075] Step 203: Obtain the scalar miss distance estimator based on the joint probability density of the echo signals in the channel.

[0076] like Figure 3 As shown, the miss distance measurement radar antenna array is located in the yoz plane. It is a 1-transmitter M-receiver antenna array, and the transmitting antenna located at the origin can also serve as the Mth receiving antenna.

[0077] In the current coordinate system, assuming the target moves at a constant velocity v in a straight line, its trajectory parameters are θ = [θ s T ,θ v T ] T , where θ s =[r,v,l] T θ represents the scalar miss distance parameter of the target relative to the origin.v =[α,β,z0] T The vector miss distance parameter represents the target's trajectory, so the target's position at time t is p(t) = [p x (t),p y (t),p z (t)] T It can be determined by θ as follows:

[0078] p x (t)=x0-(l-vt)cosαcosβ

[0079] p y (t)=y0-(l-vt)sinαcosβ

[0080] p z (t)=z0+(l-vt)sinβ

[0081] in(·) T This indicates the transpose of a matrix or vector. This represents the closest distance to the origin on the target trajectory; p0 = [x0, y0, z0] T α represents the coordinates of the miss point; l represents the distance between the target's starting position and the miss point; v represents the target's velocity; α∈[0,2π] is the ballistic deflection angle, defined as the angle between the projection of the target trajectory onto the xoy plane and the positive x-axis; β∈[-π / 2,π / 2] is the ballistic inclination angle, defined as the angle between the target trajectory and the xoy plane, and β takes a positive value when the projection of the target's trajectory onto the z-axis points to the negative z-axis direction, and a negative value otherwise.

[0082] When the sampling interval T (i.e. After discrete sampling of the analog signal, the baseband data obtained by the m-th receiving antenna in the current measurement scenario can be directly expressed as:

[0083] x m =A m s m +w m

[0084] Where A m Let w be the complex amplitude of the unknown signal in the m-th receiving channel. m The variance of the corresponding channel is Complex Gaussian white noise and each channel is independent of the others, i.e. s m =[s m (0),s m (1),…,s m (N-1)] T Let be the echo signal of the m-th receiving channel, where

[0085]

[0086] Where T m =[T x (m),T y (m),T z (m)] T T represents the coordinates of the receiving antenna m in the measurement coordinate system; M =[0,0,0] T This represents the coordinates of the transmitting and receiving antennas M in the measurement coordinate system; p(n) = [p x (n),p y (n),p z (n)] T Let ||p(n)-T| represent the position coordinates of the target at sampling time nT. m ||2 represents the distance between the target and the m-th receiving antenna at that moment.

[0087] In particular, the signal phase of the Mth receiving channel can be simplified to...

[0088]

[0089] Since the target sampling points are independent of each other, the joint probability density of the echo signal of the Mth channel is:

[0090]

[0091] Where N is the number of sampling points, (·) H σ represents the conjugate transpose of a matrix or vector. M Let M be the noise variance of the M-th channel. For A M The maximum likelihood estimate can be obtained.

[0092]

[0093] Therefore, based on the maximum likelihood criterion, the unknown parameter θ can be obtained. s =[r,v,l] T The estimator is

[0094]

[0095] The simplified scalar miss estimate is

[0096]

[0097] In this embodiment of the invention, by designing a scalar miss estimate estimator, the scalar miss parameters can be obtained first, reducing the parameter dimensionality and providing a data foundation for subsequent vector miss acquisition.

[0098] Based on any of the above embodiments, such as Figure 4 As shown, the method for obtaining the vector miss distance estimator includes:

[0099] Step 401: Set geometric constraints based on the spatial location of the target at each sampling moment during the rendezvous process obtained from the multi-channel baseband signal;

[0100] Step 402: Calculate the joint probability density of the echo signal in each channel as a function of the vector miss distance, based on the maximum likelihood estimate of the complex amplitude of the signal in each channel and the phase of the signal in each channel.

[0101] Step 403: Obtain the vector miss distance estimator based on the geometric constraints and the joint probability density of the echo signals in each channel.

[0102] In this embodiment of the invention, a matrix is ​​constructed based on the received data from the M receiving channels.

[0103] X = [x1, x2, ..., x m ,…,x M ] T

[0104] In the formula,

[0105] x m =A m s m +w m

[0106] Since the received data matrix X contains the spatial location p(n) of the target at each sampling time during the intersection process, and according to the definition of the miss point, the miss point coordinates p0 = [x0, y0, z0] T It also obeys coordinate functions

[0107]

[0108] If the above expression is meaningful, then the geometric constraints must be satisfied.

[0109] r 2 -(z0 / cosβ) 2 ≥0

[0110] That is, all parameters of the target trajectory Ξ = [θ s T ,d T p0 T ] T All of these can be obtained by θ=[θ] under the premise of satisfying geometric constraints. s T ,θ v T ] TThis is derived from the transformation, where d = [α, β] T Let θ be the direction vector of the target trajectory. In summary, as long as θ is estimated from the received data matrix X... v This allows us to obtain all parameters of the current trajectory. By repeating the derivation process of the scalar miss estimate, we can obtain the unknown vector miss parameters θ. v =[α,β,z0] T The first estimator is

[0111]

[0112] str 2 -(z0 / cosβ) 2 ≥0

[0113] Based on any of the above embodiments, such as Figure 5 As shown, the method for obtaining the vector miss distance estimator includes:

[0114] Step 501: Obtain the inherent phase difference between different receiving channels, and compensate the complex amplitude of the echo signal of each receiving channel according to the inherent phase difference between different receiving channels.

[0115] In this embodiment of the invention, the inherent phase difference between different receiving channels can be obtained through methods such as feeder calibration and anechoic chamber testing.

[0116] Step 502: Calculate the maximum likelihood estimate of the complex amplitude of the compensated echo signal;

[0117] Step 503: Calculate the corrected joint probability density of the echo signal in each channel based on the maximum likelihood estimate of the complex amplitude of the compensated echo signal and the phase of the signal in each channel;

[0118] Step 504: Set geometric constraints based on the spatial location of the target at each sampling moment during the rendezvous process obtained from the multi-channel baseband signal;

[0119] In this embodiment of the invention, the geometric constraints include:

[0120]

[0121] r 2 -(z0 / cosβ) 2 In the formula ≥0, r is the scalar miss distance, α is the trajectory deviation angle, β is the trajectory inclination angle, and p0 = [x0, y0, z0]. T The coordinates of the target's miss point.

[0122] Step 505: Obtain the vector miss distance estimator based on the geometric constraints and the modified joint probability density of the echo signal in each channel.

[0123] In this embodiment of the invention, a more accurate estimate of the vector miss distance can be obtained by supplementing the inherent phase difference information between channels.

[0124] If the inherent phase difference between different receiving channels has been obtained through methods such as feeder calibration and anechoic chamber testing, then the complex amplitude of the echo signal from each receiving channel can be uniformly compensated to...

[0125] A1 = A2 = ... = A M =A

[0126] At this point, the maximum likelihood estimate of A is

[0127]

[0128] By repeating the derivation process of the scalar miss estimate, a second estimator for the vector miss parameters with higher accuracy can be obtained.

[0129]

[0130] str 2 -(z0 / cosβ) 2 ≥0

[0131] In this embodiment of the invention, the high-speed rendezvous target trajectory parameter estimation method further includes:

[0132] If a set of miss parameters corresponds to multiple sets of trajectory parameters, then the trajectory parameter with the largest output modified joint probability density function value is selected as the optimal modified joint probability density function.

[0133] The vector miss estimate is obtained based on the optimal modified joint probability density function.

[0134] Based on the invariance of the maximum likelihood estimate, since the transformation function g in the vector parameter transformation formula η=g(θ) that transforms the miss distance parameter into the trajectory parameter is not a one-to-one function (where g includes 6-dimensional parameters θ=[θ s T ,θ v T ] T As shown in the 2D coordinate function, the definition of η that maximizes the corrected probability density function is:

[0135]

[0136] That is, the trajectory parameters that maximize the probability density after transformation are selected as the final estimation result.

[0137] In this embodiment of the invention, if the six-dimensional parameters of the target trajectory are θ = [r, v, l, α, β, z0] T The number of candidate parameters is N.r N v N l N α N β , If there are , then considering the symmetry of the modified probability density function, the computational complexity required by the algorithm provided in this invention is . The traditional direct localization algorithm based on six-dimensional parameters requires a computational complexity of... When the number of searches for each parameter dimension is similar, the algorithm proposed in this invention can reduce the computational cost by three orders of magnitude. At the same time, due to the reduction in the parameter dimension, it can also effectively avoid getting trapped in local optima.

[0138] Based on any of the above embodiments, the trajectory parameter estimation results of the high-speed rendezvous target are determined according to the output results of the scalar miss estimater and the vector miss estimater, including:

[0139] The possible range of target trajectory parameters is divided into grids according to actual needs using the grid search method.

[0140] The cost function value corresponding to each grid is calculated, and the grid point corresponding to the maximum value of the cost function is selected as the parameter estimation result of the high-speed rendezvous target trajectory.

[0141] In this embodiment of the invention, the cost function includes a scalar miss estimate, a first vector miss estimate, and a second vector miss estimate.

[0142] The possible range of the target trajectory parameters {θ s ,θ v The grid is divided according to actual needs, and the cost value corresponding to each grid is calculated by combining the cost function. The grid point corresponding to the maximum cost is selected as the final trajectory parameter estimation result, which further improves the measurement accuracy.

[0143] like Figure 6 As shown, the specific steps of the high-speed rendezvous target trajectory parameter estimation method provided in this embodiment of the invention are as follows:

[0144] (1) Store echo signal data matrix X;

[0145] (2) Select the received data vector x corresponding to the simultaneous transmission and reception channel in X. M ;

[0146] (3) with x M Using the input data, the scalar miss distance parameter estimation method is used to obtain the estimated value θ of the scalar parameter. s =[r,v,l] T ;

[0147] (4) θ s=[r,v,l] T Set to the true value of the trajectory scalar parameter;

[0148] (5) Use the initial value determination method based on prior information to obtain the optimized initial values ​​of vector parameters for X;

[0149] (6) Determine the search range of vector parameters based on the initial optimization value, and divide the search range into multiple grid points;

[0150] (7) Using the initial value of optimization as the initial value of the optimization problem, let the estimated value of the vector parameter be equal to the initial value of optimization;

[0151] (8) Determine θ = [θ s T ,θ v T ] T Does it meet the geometric constraints?

[0152] (8) If so, the miss distance parameter θ = [θ s T ,θ v T ] T Transformed into trajectory parameters and If not, the cost function value should be set to negative infinity;

[0153] (9) According to Obtain the maximum objective function value and trajectory parameter value for this grid point;

[0154] (10) Mark the current grid as processed, and record the maximum substituent objective function value and trajectory parameter value;

[0155] (11) Determine whether all grid points have been traversed?

[0156] (12) If so, select the largest value among all the cost function values ​​of all grids and output the final trajectory parameter estimate; otherwise, continue to calculate the next grid point.

[0157] Based on any of the above embodiments, in this example, the radar carrier frequency is set to 3GHz, the sampling interval is set to 10μs, the radar antenna array is 1 transmit and 5 receive, the transmitting antenna and the receiving antenna 5 are located at the origin of the coordinate system, the receiving antennas 1 to 4 are 0.3m away from the transmitting antenna and are respectively located on the +y, +z, -y, and -z axes, and the noise power of each receiving channel is set to 1. The target's miss point is set to p0 = [0.105m, -0.66m, -0.73m], and the corresponding trajectory parameters are set to θ = [0.99m, 2000m / s, 50m, 150°, 30°, -0.73m]. The simulation data were processed using the method provided in this invention (referred to as Proposed-NPC when phase is not aligned, and as Proposed-PC after phase alignment), the traditional six-dimensional direct localization method (6D-DPD, which is divided into 6D-DPD-PC method with coherent inter-channel relationships and 6D-DPD-NPC method with non-coherent inter-channel relationships), and the frequency difference of arrival method (FDOA) or Doppler frequency-phase difference history method (DP). The root mean square error of the parameter estimation results are as follows: Figures 7-14 As shown, the Monte Carlo simulation was set to 1000 times. Figures 7-14 As can be seen, the algorithm proposed in this invention approximates the theoretically optimal accuracy of the 6D-DPD method and the Cramer-Rao boundary (CRLB) with relatively small computational load, and outperforms the traditional arrival frequency difference method or Doppler frequency-phase difference history method under simulated signal-to-noise ratio conditions. The reason why the scalar miss parameter estimation accuracy of the algorithm proposed in this invention is worse than that of 6D-DPD is that the algorithm proposed in this invention only uses data from the 5th receiving channel to estimate the scalar miss parameter, while the 6D-DPD method uses data from all 5 channels. Therefore, the algorithm proposed in this invention suffers a 5-fold loss in signal-to-noise ratio gain.

[0158] The high-speed rendezvous target trajectory parameter estimation method provided in this invention reduces the computational load required by traditional direct positioning algorithms by reducing high-dimensional parameter estimation to low-dimensional parameter estimation, and avoids the impact of intermediate parameter estimation errors on the final result, thereby significantly improving the measurement accuracy of the miss distance measurement system.

[0159] The high-speed rendezvous target trajectory parameter estimation device provided by the present invention is described below. The high-speed rendezvous target trajectory parameter estimation device described below and the high-speed rendezvous target trajectory parameter estimation method described above can be referred to in correspondence.

[0160] Figure 15 This is a schematic diagram of a high-speed rendezvous target trajectory parameter estimation device provided in an embodiment of the present invention, as shown below. Figure 15 As shown, the high-speed rendezvous target trajectory parameter estimation device provided in this embodiment of the invention includes:

[0161] Receiver module 1501 is used to receive the echo signal after it has been reflected by the target;

[0162] The sampling module 1502 is used to sample the echo signal to obtain a multi-channel baseband signal;

[0163] Input module 1503 is used to input multi-channel baseband signals into the scalar miss estimate estimator and the vector miss estimate estimator;

[0164] Output module 1504 is used to determine the trajectory parameter estimation results of the high-speed rendezvous target based on the output results of the scalar miss estimater and the vector miss estimater.

[0165] The high-speed rendezvous target trajectory parameter estimation device provided in this embodiment of the invention receives the echo signal after it is reflected by the target; samples the echo signal to obtain a multi-channel baseband signal; inputs the multi-channel baseband signal into a scalar miss distance estimator and a vector miss distance estimator; and determines the high-speed rendezvous target trajectory parameter estimation result based on the output results of the scalar miss distance estimator and the vector miss distance estimator. This device can achieve higher measurement accuracy with a computational load far less than the traditional direct positioning method, thereby making the high-speed rendezvous target trajectory parameter estimation more efficient and the estimation result more accurate.

[0166] Figure 16 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 16 As shown, the electronic device may include a processor 1610, a communications interface 1620, a memory 1630, and a communication bus 1640. The processor 1610, communications interface 1620, and memory 1630 communicate with each other via the communication bus 1640. The processor 1610 can call logic instructions in the memory 1630 to execute a high-speed rendezvous target trajectory parameter estimation method. This method includes: receiving the echo signal after reflection from the target; sampling the echo signal to obtain a multi-channel baseband signal; inputting the multi-channel baseband signal into a scalar miss estimater and a vector miss estimater; and determining the high-speed rendezvous target trajectory parameter estimation result based on the output results of the scalar miss estimater and the vector miss estimater.

[0167] Furthermore, the logical instructions in the aforementioned memory 1630 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0168] On the other hand, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements a high-speed rendezvous target trajectory parameter estimation method provided by the methods described above. The method includes: receiving an echo signal after reflection from a target; sampling the echo signal to obtain a multi-channel baseband signal; inputting the multi-channel baseband signal into a scalar miss distance estimator and a vector miss distance estimator; and determining the high-speed rendezvous target trajectory parameter estimation result based on the output results of the scalar miss distance estimator and the vector miss distance estimator.

[0169] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0170] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0171] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for estimating trajectory parameters of a high-speed rendezvous target, characterized in that, include: Receive the echo signal after it has been reflected from the target; The echo signal is sampled to obtain a multi-channel baseband signal; The multi-channel baseband signal is input into the scalar miss estimate and the vector miss estimate; The trajectory parameter estimation results of the high-speed rendezvous target are determined based on the output results of the scalar miss estimater and the vector miss estimater. The estimation results of the trajectory parameters of the high-speed rendezvous target include: Scalar miss distance parameters, vector miss distance parameters, and the target's miss point coordinates; The scalar miss distance parameter includes the distance between the target's initial position and the miss point, the target's velocity, and the scalar miss distance. The vector miss distance parameters include the ballistic deflection angle, the ballistic inclination angle, and the z-coordinate value of the miss point in the measurement coordinate system; The scalar miss estimate estimator first obtains the scalar miss parameters, reducing the parameter dimensionality and providing a data foundation for subsequent vector miss estimates.

2. The method for estimating trajectory parameters of a high-speed rendezvous target according to claim 1, characterized in that, The method for obtaining the scalar off-target estimate includes: The complex amplitude and phase of the signal in a single channel can be analyzed from the baseband signal of that channel. Calculate the maximum likelihood estimate of the complex amplitude of the signal in this channel; The joint probability density of the echo signal in the channel as a function of the scalar miss distance is obtained based on the maximum likelihood estimate of the complex amplitude of the signal in the channel and the phase of the signal in the channel. A scalar miss estimate is obtained based on the joint probability density of the echo signals in the channel as a function of the scalar miss amount.

3. The method for estimating trajectory parameters of a high-speed rendezvous target according to claim 1, characterized in that, The method for obtaining the vector miss distance estimator includes: Geometric constraints are set based on the spatial location of the target at each sampling moment during the rendezvous process, obtained from multi-channel baseband signals. The joint probability density of the echo signal in each channel is calculated as a function of the vector miss distance based on the maximum likelihood estimate of the complex amplitude of the signal in each channel and the phase of the signal in each channel. A vector miss distance estimator is obtained based on the geometric constraints and the joint probability density of the echo signals in each channel.

4. The method for estimating trajectory parameters of a high-speed rendezvous target according to claim 1, characterized in that, The method for obtaining the vector miss distance estimator includes: Obtain the inherent phase difference between different receiving channels, and compensate for the complex amplitude of the echo signal of each receiving channel based on the inherent phase difference between different receiving channels; Calculate the maximum likelihood estimate of the complex amplitude of the compensated echo signal; The corrected joint probability density of the echo signal in each channel is calculated based on the maximum likelihood estimate of the complex amplitude of the compensated echo signal and the phase of the signal in each channel. Geometric constraints are set based on the spatial location of the target at each sampling moment during the rendezvous process, obtained from multi-channel baseband signals. A vector miss distance estimator is obtained based on the geometric constraints and the modified joint probability density of the echo signal in each channel.

5. The high-speed rendezvous target trajectory parameter estimation method according to claim 4, characterized in that, Also includes: If a set of miss parameters corresponds to multiple sets of trajectory parameters, then the trajectory parameter with the largest output modified joint probability density function value is selected as the optimal modified joint probability density function. The vector miss estimate is obtained based on the optimal modified joint probability density function.

6. The method for estimating trajectory parameters of a high-speed rendezvous target according to claim 1, characterized in that, The step of determining the trajectory parameter estimation results of the high-speed rendezvous target based on the output results of the scalar miss estimater and the vector miss estimater includes: The possible range of target trajectory parameters is divided into grids according to actual needs using the grid search method. The cost function value corresponding to each grid is calculated, and the grid point corresponding to the maximum value of the cost function is selected as the parameter estimation result of the high-speed rendezvous target trajectory.

7. A high-speed rendezvous target trajectory parameter estimation device, applicable to the high-speed rendezvous target trajectory parameter estimation method according to any one of claims 1 to 6, characterized in that, include: The receiving module is used to receive the echo signal after it has been reflected from the target. The sampling module is used to sample the echo signal to obtain a multi-channel baseband signal; The input module is used to input the multi-channel baseband signal into the scalar miss estimate and the vector miss estimate; The output module is used to determine the trajectory parameter estimation results of the high-speed rendezvous target based on the output results of the scalar miss estimater and the vector miss estimater.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the high-speed rendezvous target trajectory parameter estimation method as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the high-speed rendezvous target trajectory parameter estimation method as described in any one of claims 1 to 6.

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