Linrang Zhang

Signal Fusion-Based Algorithms to Discriminate Between Radar Targets and Deception Jamming in Distributed Multiple-Radar Architectures

The potential abilities of distributed multiple-radar architectures in the electronic counter-countermeasure are analyzed based on the difference between target echoes and deception jamming in spatial scattering properties. The deception signals received by different receivers are fully correlated, while the correlation of target echoes varies gradually with the interval of view angles. According to this difference, the thought of signal fusion is first adopted and a corresponding algorithm is proposed to discriminate the deception jamming from radar targets in the Neyman-Pearson sense. In this algorithm, active false targets are identified by correlation tests between arbitrary two targets complex envelopes in different receivers. To evaluate its discrimination performance, the theoretical expression for the rejection probability of false targets is derived. Simulations verify the feasibility of the new algorithm and its performance improvement over the existing data fusion-based methods. The merit of the method lies in that it can discriminate deception signals generated by arbitrary modulation and can be used in series with data fusion-based methods to improve discrimination performance further.

Study of Multistatic Radar Against False Targets Jamming Using Spatial Scattering Properties

This paper presents a discrimination method of deception false targets in multistatic radar system using signal fusion. Based on the difference in spatial scattering properties between physical targets and false targets, correlation test is used on the complex envelope sequences to identify false targets, which is formulated as a problem of likelihood ratio test in the Neyman-Pearson sense. The simulation results verify the efficiency of the approach to discriminate false targets on the premise of the acceptance probability of physical targets.

Chaotic Discrete Frequency Coding Waveform Design for MIMO Radar

Based on the good correlation property of chaotic discrete frequency coding waveform (CDFCW), the method is proposed to increase the point target and close small target detection performance for multiple-input multiple-output (MIMO) radar. CDFCW can be generated by uniform quantifying and discrete frequency coding from chaotic sequence. Comparing the correlation property of four CDFCWs, the longer Tent discrete frequency coding waveform is chosen to increase the point target detection performance of MIMO radar. Meanwhile, the signal processing model of MIMO radar using CDFCW is built, multiple pulse compression accumulation can help to reduce the cross-correlation and auto-correlation side lobes of chaotic waveforms effectively, and the point target detection performance for MIMO radar is increased, especially for the close small target. Finally, simulation results show the effectiveness of the method.

A novel method of using chaotic sequences in MIMO radar for multiple targets detection

Based on the sensitive dependence on initial conditions and good auto-correlation of chaotic sequences, a method is proposed to increase the resolution of multiple-input multiple-output (MIMO) radar for multiple targets detection with chaotic sequences. Chaotic waveform set can be generated by chaotic sequences from different initial values. It is uncorrelated between auto-correlation sidelobes of different chaotic waveforms, at the same time, it is uncorrelated between cross-correlation of different chaotic waveforms too. Therefore, multiple pulse compression accumulation can help to reduce auto-correlation sidelobes and cross-correlation effects in MIMO radar effectively, the output has low peak sidelobe value and the resolution of multiple targets detection is increased. Finally, simulation results show the effectiveness of this method.