Study On Moving Target Detection And Tracking Methods Of Airborne MIMO Radar

The airborne MIMO radar can improve the performance of anti-interception of radar signal and low velocity target detection. Rational design of orthogonal signals is a fundamental research question in MIMO radar field. The problem of slowly moving target detection in the traditional radar can be solved, the blind velocity can be reduced and the clutter suppression properties can be improved through the MIMO radar which uses the high quality orthogonal signals. Additionally, the track before detect, which makes full use of radar measurement data, can achieve target tracking and detection in low SNR. The DP-TBD algorithm, which changes the whole process into a multi-stage optimization problem, provides a new way to detect dim moving target. Good detection and tracking performance may be achieved by using the DP-TBD algorithm to process the airborne MIMO radar data.Due to the DDMA signals, which have good correlation properties, have the questions of the Doppler ambiguity and the blind velocity, a method changing the Doppler frequency offset is presented to solve the blind velocity, which makes different transmission channels’ clutter to have less overlap in the same Doppler channel. In order to effectively reduce the computation of DP-TBD algorithm and correctly associate with the targets track, an improved DP-TBD algorithm based on association velocity is presented. Through the inter-related speed information, the search window range is reduced and target track is better associated. Paper can be summarized as follows:1. The performance of orthogonal signals is analyzed in terms of the signal correlation and the clutter cancellation. Firstly, the generalized airborne MIMO radar signal model is created. Then the airborne MIMO radar SNR is analyzed under this model. Finally, the clutter characteristic of the airborne MIMO radar is analyzed by the simulation.2. A method changing the doppler frequency offset is presented to solve the doppler ambiguity and the blind velocity existed in the DDMA signals. Firstly, the two kinds of equivalence mode which are used to reduce the processing dimension in airborne MIMO radar is analyzed. Then the clutter suppression performance between MIMO and SIMO is compared by the simulation. Finally, the DDMA signals are optimized by this method presented in this paper. Experimental results for simulation data demonstrate that the DDMA signals optimized can improve the performance of minimum detectable velocity and the clutter suppression properties.3. In order to effectively reduce the computation of DP-TBD algorithm and correctly associate with the targets track, a improved DP-TBD algorithm based on association velocity is presented. Firstly, the basic principles of DP-TBD algorithm are studied. Then the concept of association velocity is explained. And describe how it reduces the amount of computation and how it associates with the targets track correctly. Finally, the simulation results demonstrate the effectiveness of the improved method to solve the above problems.