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Design method of radar maneuvering target tracking waveform

A technology of maneuvering target tracking and waveform design, applied in the field of radar communication, can solve problems such as low accuracy and weak tracking robustness, and achieve the effects of improving tracking accuracy, avoiding mismatch of maneuvering targets, and good freedom

Active Publication Date: 2017-11-24
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.

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  • Design method of radar maneuvering target tracking waveform
  • Design method of radar maneuvering target tracking waveform
  • Design method of radar maneuvering target tracking waveform

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Experimental program
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specific Embodiment approach 1

[0027] Specific implementation manner 1: The method for designing radar maneuvering target tracking waveforms given in this implementation manner is specifically carried out according to the following steps:

[0028] Step 1: Construct a motion model for the maneuvering target;

[0029] Step 2: Calculate the weights of the filter update matrix corresponding to the motion model;

[0030] Step 3: Calculate the mixed input state of the motion model and the corresponding estimated error covariance matrix;

[0031] Step 4. Use linear or non-linear 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 the fusion estimation error covariance matrix;

[0033] Step 6. Obtain the transmission waveform rotation parameters based on the fusion estimation error covariance matrix, and use the fractional Fourier transform to rota...

specific Embodiment approach 2

[0035] Specific implementation manner 2: This implementation manner is different from the specific implementation manner one in that the construction of a motion model for a maneuvering target in the first step is specifically:

[0036]

[0037] The formula includes the target state equation x(k+1)=F j (x(k))+w j (k) and the 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 the X and Y directions, z(k) is the measurement vector; j ∈{1,...,s} represents the model number in the model library, and s is the number of models; when the above formula represents a linear motion model, F j (·) and H j (·) is the linear transition matrix, when the nonlinear motion model is F j (·) and H j (·) represents a nonlinear function; w j (k) means that the mean is zero and the covariance matrix is ​​Q j Gaussian process noise, v(k) represents the measurement noise with a mean value of zero an...

specific Embodiment approach 3

[0041] Specific embodiment three: This embodiment is different from the specific embodiment two in that the second step of calculating the weight of the filter update matrix corresponding to the motion model specifically includes the following steps:

[0042] For the state vector x, suppose the corresponding local unbiased filter estimates of s sub-models are Represents the local estimation error, Represents the i-th motion model The target state estimation error covariance matrix, Represents the motion model with The estimated error cross-covariance matrix of, and i≠j has Where E(·) is the expected value function; local unbiased filter estimation Can be regarded as the i-th motion model The corresponding filter's measurement of x is:

[0043]

[0044] Then you can define:

[0045]

[0046] among them:

[0047]

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

[0049]

[0050] Unbiased knowledge which is I n Represents the n×n-dimensional unit matrix, e=[I n ... I n ] T Is a full-rank matrix; ...

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Abstract

The invention belongs to the technical field of radar communication and particularly relates to a design method of a radar maneuvering target tracking waveform. The method includes: building a movement model for a maneuvering target, calculating filter update matrix weight, the mixed input state of the movement module and a corresponding estimation error covariance matrix, using a linear or nonlinear filtering algorithm to acquire the local unbiased filter estimation value and target state estimation error covariance matrix of each submodel, performing compound matrix updating to obtain optimal state estimation and fusion estimation error covariance matrix, acquiring transmission waveform rotation parameters on the basis, using fractional Fourier transformation to rotate the waveform set by a user to obtain a new measuring error ellipse and transmission waveform, and performing Markov transition probability matrix updating to achieve good tracking precision. By the design method applicable to the radar communication technology, the problem that maneuvering target tracking is poor in robustness and low in accuracy is solved.

Description

Technical field [0001] The invention belongs to the technical field of radar communication, and specifically relates to a method for designing a tracking waveform of a radar maneuvering target. Background technique [0002] The state of maneuvering targets in the battlefield often presents the characteristics of randomness and diversity, making it difficult for traditional radars to track effectively, which has become a difficult point in current research. Most studies start from the receiving end data processing, focusing on target state modeling and filtering algorithm improvement (see the literature: New interacting multiple model algorithms for the tracking of 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); Ignoring the target tracking accuracy...

Claims

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Application Information

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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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