Robust Beamforming Based on Covariance Matrix Reconstruction in FDA-MIMO Radar to Suppress Deceptive Jamming.

Fuhai Wan,Zhenrong Zhang,Jingwei Xu

doi:10.3390/s22041479

Fuhai Wan, Zhenrong Zhang + Show 1 more

Open Access

https://doi.org/10.3390/s22041479

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Abstract

Frequency diverse array (FDA)-multiple-input multiple-output (MIMO) radars can generate a range-angle two-dimensional transmit steering vector (SV), which is capable of suppressing mainbeam deceptive jamming in the transmit–receive frequency domain by utilizing additional degrees of freedom (DOFs) in the range dimension. However, when there are target SV mismatch, covariance matrix estimation error and target contamination, the jamming suppression performance degrades severely. In this paper, a robust adaptive beamforming algorithm for anti-jammer application based on covariance matrix reconstruction is proposed in FDA-MIMO radar. In this method, the residual noise is further determined by using the spatial power spectrum estimation approach, which results in improved estimation accuracy of the signal covariance matrix and the desired target SV. The jamming SV is obtained from vectors in the intersection of two subspaces (namely, the signal-jamming subspace derived from the sample covariance matrix (SCM) and the jamming subspace generated from the jamming covariance matrix) by an alternating projection algorithm. Furthermore, the jamming power is obtained by exploiting the orthogonality between the different SVs. With the obtained parameters of target and jamming, the optimal adaptive beamformer weight vector is calculated. Simulation results demonstrate that the proposed algorithm can cope with the mainbeam deceptive jamming suppression under various model mismatches and has excellent performance over a wide range of signal-to-noise ratios (SNRs).

Highlights

With the invention of electronic countermeasures technologies, active deceptive jamming has caused significant repercussions such as impaired information collecting capabilities and resource occupancy in radar systems [1,2]
Jammers equipped with digital radio frequency memory (DRFM) can form active deceptive jamming that is coherent with real target echo by intercepting, sampling, parameter modulation, and forwarding radar signals, causing the radar system to misidentify false targets as real targets, resulting in the loss of real target and air situation anomalies [3]
We proposed a deceptive jamming-resistant adaptive beamforming approach based on Frequency diverse array (FDA)-multiple-input multiple-output (MIMO) radar, which eliminates the adverse impacts of range-angle mismatch and interference-plus-noise covariance matrix (IPNCM) error

Summary

Introduction

With the invention of electronic countermeasures technologies, active deceptive jamming has caused significant repercussions such as impaired information collecting capabilities and resource occupancy in radar systems [1,2]. Jammers equipped with digital radio frequency memory (DRFM) can form active deceptive jamming that is coherent with real target echo by intercepting, sampling, parameter (time delay, Doppler frequency) modulation, and forwarding radar signals, causing the radar system to misidentify false targets as real targets, resulting in the loss of real target and air situation anomalies [3]. There are two types of mainbeam deceptive jamming. The first is jamming that locates inside the main lobe, typical applications such as pods and decoys, which protect the target by forwarding intercepted radar signals that form a coherent scattering source with the signals dispersed directly by the target. Since the characteristics of such mainbeam deceptive jamming and target signal in frequency, temporal, spatial and polarization domains are essentially the same, conventional radar with corresponding algorithms become invalid in anti-jamming, calling for novel scheme of radar and signal processing algorithms

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Conclusion