SMSP Mainlobe Jamming Suppression with FDA-MIMO Radar Based on FastICA Algorithm

Abstract

In the electronic warfare environment, the performance of ground-based radar target search is seriously degraded due to the existence of smeared spectrum (SMSP) jamming. SMSP jamming is generated by the self-defense jammer on the platform, playing an important role in electronic warfare, making traditional radars based on linear frequency modulation (LFM) waveforms face great challenges in searching for targets. To solve this problem, an SMSP mainlobe jamming suppression method based on a frequency diverse array (FDA) multiple-input multiple-output (MIMO) radar is proposed. The proposed method first uses the maximum entropy algorithm to estimate the target angle and eliminate the interference signals from the sidelobe. Then, the range-angle dependence of the FDA-MIMO radar signal is utilized, and the blind source separation (BSS) algorithm is used to separate the mainlobe interference signal and the target signal, avoiding the impact of mainlobe interference on target search. The simulation verifies that the target echo signal can be effectively separated, the similarity coefficient can reach more than 90% and the detection probability of the radar is significantly enhanced at a low signal-to-noise ratio.

Echo Preprocessing-Based Smeared Spectrum Interference Suppression

“…Equations ( 11) and (26) indicate that the PC outputs of the SMSP interference before and after echo preprocessing are the superposition of the PC outputs of the interference sub-waveforms. In addition, the properties of the PC output of the SMSP interference are summarized in Table 2.…”

“…Subsequently, the target cannot be detected and the corresponding distance and Doppler information cannot be obtained. In Figure 7b, since the output of the SMSP interference after the PC is related to the slow-time according to (26), the interference cannot further obtain CI gain. Moreover, the range and Doppler frequency of the target are shown as 30 km and 250 Hz, respectively, which are consistent with the parameter settings.…”

“…Therefore, it has generated attention and research activity among many experts and scholars. The existing methods for SMSP interference suppression can be generally divided into three categories, namely, transform domain filtering [15][16][17], signal reconstruction [18][19][20][21][22], and multi-channel signal separation [23][24][25][26]. In [15], the echo signal is transformed into the linear canonical transform (LCT) domain, and the target signal is extracted by narrowband filtering to achieve interference suppression.…”

“…However, the short-time Fourier transform may not be able to accurately obtain the frequency modulation (FM) information of the target and interference under low signal-to-noise ratio (SNR) scenarios. Blind source separation technology is applied in [23][24][25][26], in which polarization domain information is introduced in [23,24], and a frequency diverse array radar system is introduced in [25,26]. But these methods are only applicable to multi-channel radar.…”

A Novel Complex-Valued Blind Source Separation and Its Applications in Integrated Reception

“…Blind source separation (BSS) [1,2] aims to recover or reconstruct the source signal using observed data from the receiver channel, even when the source signal and mixing characteristics are unknown. BSS, as a powerful technology in signal processing, has played a crucial role in various domains, including speech separation [3][4][5], wireless communication [6][7][8], anti-main lobe jamming [9][10][11][12][13], and direction of arrival (DOA) estimation [14,15]. BSS has also provided innovative ideas for ongoing research in integrated arrival (DOA) estimation [14,15].…”