Bistatic Mimo Radar Angle Estimation Technology Research

In modern warfare, anti-radiation missiles, electronic interference, over-low altitude penetration and stealth target are becoming the threats that radar has to face. In fact, traditional monostatic radar has been unable to survive. Fortunately, bistatic radar can overcome these "four-anti" threats, and it possesses many advantages, moreover, the introduction of MIMO technology enables it to show the capability of anti-saturation-attack and precision tracking. At present, the study on bistatic MIMO radar has already been transferred from basic theoretical research to analysis of radar performance under specific background. As the battlefield environment is complicated and various, how to improve the performance of weak target angle estimation under strong clutter and target background, and how to detect and track the target effciently, are the hot issues of bistatic MIMO radar.This paper mainly focuses on the weak target angle estimation problem of bistatic MIMO radar under complex background. The main work is bistatic MIMO radar clutter modeling and weak target angle estimation method under complex background. The main contents are as follows:1. The basic principle and signal processing framework of bistatic MIMO radar are introduced in details. In this paper, we discusses the characteristics advantages and key technology of bistaic radar system.2. According to the clutter characteristics of bistatic MIMO radar, a clutter modeling method is proposed, and the differences between bistatic MIMO radar and traditional clutter modeling method are analyzed. A new clutter units division method is also presented. Simulation and analysis of the clutter spectrums are shown at last, which proves that the clutter modeling method is efficient.3. Aiming at the problem of angle estimation for bistatic MIMO radar, studies on the application of the traditional MUSIC algorithm, parallel factor algorithm and the multistage Wiener filter algorithm are implemented. The transmitting and receiving angle estimation performances of these three algorithms under complex background are simulated and analyzed. 4. Aiming at the sharp degrading problem of weak target angle estimation in the context of the strong target scenario, we propose a MSWF algorithm based on the expansion of the noise subspace by combining the existing MUSIC algorithm which is based on the expansion of the noise subspace with the multistage Wiener filtering algorithm which is based on the data level. The performance of weak target angle estimation employed this algorithm is simulated and analyzed.