Direction finding method of bistatic MIMO radar based on immune cuckold search under impulsive noise

Abstract

The invention discloses a direction finding method of bistatic MIMO radar based on immune cuckold search under impulsive noise. The method is performed through the following steps: acquiring sampling data; conducting infinite norm normalization to obtain a weighted signal covariance matrix; setting parameters and initializing belief space; Initializing the bird eggs, calculating their fitness and arranging them in a descending order so as to find the optimal bird eggs; preparing vaccines through cultural mechanisms; using the Levy flight to update the bird eggs, calculating their fitness and using greedy selection for strategy choice; calculating their fitness and using greedy selection for strategy choice by reconstructing a new nest and updating the bird eggs; according to descending arrangement of the fitness values, vaccinating the poor bird eggs, calculating the fitness and simulating the choice of an annealing mechanism; according to descending arrangement of the fitness values, finding and recording the optimal bird eggs; and determining if the maximum number of iterations has been reached and if not, outputting the DOD and DOA estimates. The method has the advantages of a high convergence speed, high estimation accuracy, a strong de-coherence ability, a good anti-noise ability and great prospects for wide applications.

Description

technical field [0001] The present invention relates to a radar direction finding method, in particular to a bistatic multiple input multiple output (Multiple Input Multiple Output, MIMO) radar direction finding method. Background technique [0002] MIMO radar has become a popular research topic. It is a new type of radar system proposed after the MIMO theory and space-time coding theory are applied to communication systems and made a major breakthrough. It is different from the traditional phase-controlled Compared with array radar, MIMO radar can overcome fading effect and improve spatial resolution, and improve detection and estimation performance through waveform diversity. At present, according to the spatial distribution of radar antennas, MIMO radars can be divided into two types: centralized MIMO radars and distributed MIMO radars, namely so-called monostatic MIMO radars and bistatic MIMO radars. The former concept was proposed by Bliss and Forsythe of the Massachus...

AI Technical Summary

Problems solved by technology

Applying the maximum likelihood algorithm to the DOD and DOA estimation of bistatic MIMO radar targets, it has excellent performance in the case of low signal-to-noise ratio, small number of snapshots and coherent sources, but ML estimation involves a multidimensional nonlinearity Optimization problems, the amount of calculation is quite large

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