Mimo Radar Target And Performance Analysis

MIMO radar is a new type of radar system, as a result of the virtual array yuan, waveform diversity, space diversity technology application, making the MIMO radar target detection performance than traditional radar more superior, so the concept of MIMO radar is put forward has been widespread concern at home and abroad. Virtual array technology makes the MIMO radar in having less actual array cases, virtual a large number of virtual array, improve the detection performance of radar target and the Angle resolution. Space diversity technology makes the MIMO radar can through the different Angle observation target, compared with the traditional radar is concerned, can be a very good inhibition target RCS flicker. According to the array configuration is different, the MIMO radar can be divided into single base MIMO radar, double base MIMO radar and base MIMO radar. This paper mainly studies the bistatic MIMO ray, and then according to the array configuration is different, analyzed respectively based on the uniform line the list of bistatic MIMO radar and based on the round the list of MIMO radar.In the doppler frequency is very large, at the receiving end matched filter will produce mismatch phenomenon. This paper studies the doppler frequency based on phase coding for the MIMO radar signal processing and the influence of parameter estimation, and derived the filter output main sidelobe ratio and doppler frequency change relations.According to the distribution of the linear array bistatic MIMO radar, this paper analyzes the sending and receiving signal model. Then analysis the receiving end is matched filter group of signal processing process, elaborates several beam forming principle, and the direction of the beam is more than the figure, and give out the simulative result.According to the distribution of the circular column bistatic MIMO radar, this paper studies the radar system of three dimensional positioning. Aiming at this issue, this paper first using ESPRIT algorithm estimates target receiving Angle. Then the receiving end signal separation, using the combined model incentive hair and UCA-ESPRIT algorithm for target azimuth and pitching Angle relationship. Using the three angles of goal orientation, and in the light of the algorithm to do the target of GDOP simulation validated its usability.