Iteration-adaptive-algorithm-based method for detecting coherent MIMO radar target

Abstract

The invention discloses an iteration-adaptive-algorithm-based method for detecting a coherent MIMO radar target. First, a relation model among a first echo signal, a transmitting signal reflection coefficients and noise interference of the target is confirmed, wherein the relation model is observed on the n observation point, secondly, the relation model is linearized, further the reflection coefficients of the target are initialized through a delayed superposition DAS algorithm, and finally, a bayesian model order selecting tool is used for optimizing the reflection coefficients of the target. An iteration adaptive algorithm can effectively solve existing encountered problems of moving target parameter detection and greatly improves accuracy of detecting of the coherent MIMO radar moving target.

Description

technical field [0001] The invention relates to a MIMO radar target detection method, in particular to a coherent MIMO radar target detection method based on an iterative adaptive algorithm. Background technique [0002] Compared with phased array radar, multiple-input multiple-output (MIMO) radar has higher detection performance for weak targets, good anti-stealth effect and good anti-destruction ability, which has attracted more and more scholars to study it. MIMO radar can generally be divided into two categories: the first category is statistical MIMO radar or incoherent MIMO radar, that is, the antenna elements are sparsely distributed in space, so that space diversity gain can be obtained, and the influence of target RCS fluctuation on radar detection performance can be effectively overcome; The second type is coherent MIMO, which can form a large virtual array aperture with fewer antenna arrays, which improves the radar angular resolution and interference suppression ...

AI Technical Summary

Problems solved by technology

[0005] The coherent MIMO radar space-time adaptive processing method in the prior art has a sharp increase in the degree of freedom of clutter due to suppressive interference in a complex electromagnetic environment, and the degree of freedom of the traditional adaptive processing algorithm (STAP) cannot meet the requirements of clutter suppression ; Deceptive interference leads to severe non-uniform distribution of clutter, making it impossible for the STAP algorithm to obtain enough training samples that satisfy the independent and identical distribution conditions

In addition, the existing STAP needs auxiliary data to estimate the basic data of the clutter and noise harmonic matrix, but auxiliary data with high accuracy is difficult to obtain, especially for the non-uniform clutter environment

In order to reduce the dependence on auxiliary data, space-time adaptive algorithms that do not require auxiliary data, such as the DAS method, are proposed, but such methods face the problem of low resolution and high side lobes

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