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A Waveform Design Method for Radar Maneuvering Target Tracking

A maneuvering target tracking and waveform design technology, applied in the field of radar communication, can solve the problems of poor tracking robustness and low accuracy, and achieve the goal of avoiding maneuvering target mismatch, improving tracking accuracy, and avoiding position error and speed error. Effect

Active Publication Date: 2019-06-18
HARBIN INST OF TECH AT WEIHAI +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention provides a radar maneuvering target tracking waveform design method to solve the problem that the existing technology ignores the correlation between the position error and the velocity error of each model, resulting in weak tracking robustness and low accuracy.

Method used

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  • A Waveform Design Method for Radar Maneuvering Target Tracking
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  • A Waveform Design Method for Radar Maneuvering Target Tracking

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Experimental program
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specific Embodiment approach 1

[0027] Specific implementation mode one: a kind of radar maneuvering target tracking waveform design method provided in this implementation mode is specifically carried out according to the following steps:

[0028] Step 1, constructing a motion model for the maneuvering target;

[0029] Step 2, calculating the filter update matrix weight corresponding to the motion model;

[0030] Step 3, calculating the mixed input state of the motion model and the corresponding estimation error covariance matrix;

[0031] Step 4, using a linear or nonlinear filtering algorithm to obtain the local unbiased filter estimation and target state estimation error covariance matrix of each sub-model;

[0032] Step 5. Update the composite matrix to obtain the optimal fusion state estimation and fusion estimation error covariance matrix;

[0033] Step 6. Based on the fused estimation error covariance matrix, the transmit waveform rotation parameters are obtained, and the user-set waveform is rotate...

specific Embodiment approach 2

[0035] Specific embodiment two: the difference between this embodiment and specific embodiment one is: in the step one, constructing a motion model for the maneuvering target is specifically:

[0036]

[0037] The formula includes the target state equation x(k+1)=F j (x(k))+w j (k) and measurement equation z(k)=H j(x(k))+v(k); x(k) represents the target state vector at time k, the dimension is n×1, including the position and speed state in X and Y directions, z(k) is the measurement vector; j ∈{1,...,s} represents the serial number of the model in the model library, s is the number of models; when the above formula represents a linear motion model, F j ( ) and H j ( ) is a linear transfer matrix, F in nonlinear motion model j ( ) and H j ( ) represents a nonlinear function; w j (k) means the mean is zero and the covariance matrix is ​​Q j Gaussian process noise, v(k) represents the measurement noise with zero mean and covariance matrix R; represents the jth motion ...

specific Embodiment approach 3

[0041] Specific embodiment three: the difference between this embodiment and specific embodiment two is that the calculation of the filter update matrix weight corresponding to the motion model in step two specifically includes the following steps:

[0042] For the state vector x, let the corresponding local unbiased filter estimates of the s sub-models be represents the local estimation error, Indicates the i-th motion model The target state estimation error covariance matrix of , Indicates the motion model and The estimated error cross-covariance matrix of , and when i≠j has Where E(·) is the function to obtain the expected value; local unbiased filter estimation can be regarded as the i-th motion model The corresponding filter measures x, that is:

[0043]

[0044] It can then be defined:

[0045]

[0046] in:

[0047]

[0048] e=[I n ...I n ] T

[0049]

[0050] know by unbiased which is I n Represent n×n dimension identity matrix, e...

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Abstract

A radar maneuvering target tracking waveform design method belongs to the technical field of radar communication, and specifically relates to a radar maneuvering target tracking waveform design method. The present invention first constructs a motion model for the maneuvering target, calculates the filter update matrix weight, the mixed input state of the motion model, and the corresponding estimated error covariance matrix, and then uses a linear or nonlinear filtering algorithm to obtain the local unbiased filtering of each sub-model The error covariance matrix of device estimation and target state estimation is performed, and the composite matrix is ​​updated to obtain the optimal fusion state estimation and fusion estimation error covariance matrix. On this basis, the transmission waveform rotation parameters are obtained, and the fractional Fourier transform is used to rotate the user Set the waveform to obtain a new measurement error ellipse and launch waveform, and finally update the Markov transition probability matrix to achieve better tracking accuracy. The invention solves the problems of weak robustness and low accuracy in maneuvering target tracking. The invention can be applied to radar communication technology.

Description

technical field [0001] The invention belongs to the technical field of radar communication, and in particular relates to a waveform design method for radar maneuvering target tracking. Background technique [0002] The status of maneuvering targets in the battlefield often presents randomness and diversity, which makes it difficult for traditional radars to effectively track them, which has become a difficulty in current research. Most studies start from data processing at the receiving end, focusing on target state modeling and filtering algorithm improvement (see literature: New interacting multiple model algorithms for the tracking of the maneuvering target, FU X, JIA Y, DU J, et al.; IET control theory&applications ,2010,4(10):2184-2194; Dynamic waveform selection for maneuvering targettracking in clutter, WANG Jiantao, QIN Yuliang, WANG Hongqiang, et al; IET Radar,Sonar&Navigation,2013,7(7):815-825); Neglecting that the target tracking accuracy is not only related to t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S7/41
CPCG01S7/41
Inventor 赵宜楠冯翔赵占锋周志权
Owner HARBIN INST OF TECH AT WEIHAI
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