MIMO radar parameter estimation method based on truncation correction SL0 algorithm

A parameter estimation and radar technology, which is applied in the field of MIMO radar target parameter estimation, can solve problems such as failure, and achieve the effects of improving ill-conditionedness, improving calculation accuracy, and improving accuracy and speed

Active Publication Date: 2017-08-18
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

[0004] Purpose: In order to overcome the problem that the SL0 algorithm is invalid due to the ill-conditionedness of the perception matrix in the MIMO ra

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  • MIMO radar parameter estimation method based on truncation correction SL0 algorithm
  • MIMO radar parameter estimation method based on truncation correction SL0 algorithm
  • MIMO radar parameter estimation method based on truncation correction SL0 algorithm

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Embodiment Construction

[0045] The present invention will be further described below in conjunction with the accompanying drawings.

[0046] A method for estimating MIMO radar parameters based on the truncation modified SL0 algorithm, comprising the steps of:

[0047] 1. MIMO radar receiving signal model

[0048] Assume that the transmit array and receive array of the MIMO radar are respectively composed of M t transmitting elements and M r consists of receiving array elements, where the distance between the transmitting array element and the receiving array element is d t and d r . The transmit signal matrix of the transmit array is expressed as

[0049]

[0050] In the formula, s m =[s m (1), s m (2),...,s m (N)] T Indicates the transmit signal of the mth transmit array element, and N is the length of the transmit signal.

[0051] Divide the radar target detection scene into Z (Z=P·K·H) discrete range-angle-Doppler units, where P is the number of range units, K is the number of angle ...

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Abstract

The invention discloses an MIMO radar parameter estimation method based on a truncation correction SL0 algorithm, comprising the following steps: first, improving a pathological MIMO radar sensing matrix, and getting a non-pathological sensing matrix from a corrected singular value and corresponding left and right singular matrixes thereof through SVD inverse transformation; then, estimating the parameters of an MIMO radar target using an SL0 algorithm, and replacing the pseudo-inverse of the pathological sensing matrix with the pseudo-inverse of the obtained non-pathological sensing matrix in calculation of the initial value and the gradient projection value; and finally, determining the angle, distance and Doppler information of the MIMO radar target according to the position of a nonzero element in a target scene vector estimated value obtained using the SL0 algorithm. The problem on how to estimate the parameters of an MIMO radar target under a pathological sensing matrix is solved. The complexity of MIMO radar target parameter estimation is reduced. Engineering implementation is facilitated. The method is suitable for a target detection occasion requiring high real-time characteristic in modern warfare.

Description

technical field [0001] The invention relates to a MIMO radar target parameter estimation method based on a truncation correction SL0 algorithm, and belongs to the technical field of MIMO radar target parameter estimation. Background technique [0002] Multiple Input and Multiple Output Radar (Multiple Input and Multiple Output, MIMO) is a new radar system. Compared with phased array radar, MIMO radar adopts waveform diversity technology, improves target resolution, enhances system parameter identification ability, and has great advantages in parameter estimation, noise suppression and target detection. Compressed Sensing (CS) is an emerging theory of signal sampling and reconstruction, different from the traditional Nyquist sampling theorem, it can achieve sparse signal reconstruction by randomly sampling a small number of observations, is Current research hotspots in the field of signal processing. In the actual radar detection area, the target is sparsely distributed, an...

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Application Information

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IPC IPC(8): G01S7/41
CPCG01S7/41
Inventor 陈金立李伟李家强
Owner NANJING UNIV OF INFORMATION SCI & TECH
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