Study On STAP In Heterogeneous Environment And Parameter Estimation For MIMO Radar

The ground clutter return is usually very strong and it has an impact on target detection when the airborne radar operating at look-down mode. Traditional one-dimensional Doppler filter or spatial filter is unable to effectively suppress the clutter spreads in Doppler and spatial domain. Space-time adaptive processing(STAP) is a two-dimensional adaptive filter that combines multiple spatial channels and coherent pulses to realize clutter suppression. It can effectively suppress the clutter and simultanousely get a coherent processing gain for the interested target. Therefore, STAP has become a key technique for clutter suppression in ariborne radar. Theoretically, in order to get an anticipated STAP performance, the number of independent and identical distributed(IID) training samples should be larger than two times of system degree of freedom(DOF). However, the real clutter environment is usually heterogeneous, that makes the training data do not satisfy the IID assumption. Hence, the performance on clutter suppression obtained by traditional STAP will be significantly degraded in heterogeneous environment. It is very important to improve the performance on clutter suppression obtained by STAP in heterogeneous environment.Recently, the concept of multiple-input multiple-output(MIMO) radar has been proposed. The MIMO radar has the ability to transmit arbitrary waveform from each antenna element. Compared with the traditional phased array radar, the MIMO technique can result in significantly increased system DOF, extended array aperture and improved performance on parameter estimation. However, the computational complexity of conventional parameter estimation algorithms will increase with the increased system DOF, and the performance of parameter estimation will be significantly degraded in the low signal-to-noise ratio and small samples circumstance. How to improve the performance of parameter estimation in undesired environment, and meanwhile decrease the computation load is valuable for MIMO radar real application.The main work of this dissertation can be summarized as follows:1. The problem of range-dependent clutter suppression for non-sidelooking airborne radar is studied. For airborne non-sidelooking array radar, the clutter spectrum varies with range due to the non-sidelooking array configuration. That is to say, the clutter is range-dependent. The range dependency has a strong impact on STAP for lack of IID secondary data. It is more complicated when the radar system operating at high pulse repeatition frequency. The short-range clutter is coupled with long-range clutter due to range ambiguity and clutter suppression becomes more difficult. A novel orthogonal-waveform-based elevation adaptive beamforming method is proposed to suppress range-dependent short-range clutter, and the residual range-independent long-range clutter could be suppressed by azimuth-Doppler STAP. The proposed elevation beamformer can provide excellent performance on short-range clutter suppression and protect long-range target from nulling. After suppression of the range dependent short-range clutter, the range independency of clutter samples is enhanced evidently. Hence, the clutter suppression performance obtained by azimuth-Doppler STAP methods could be improved dramatically.2. The problem of clutter suppression in heterogeneous environment based on direct data domain(DDD) STAP is considered. The power heterogeneity leads to either over or under nulling of the clutter. The net effect of discrectes is typically an increase in false-alarm rate. The presence of dense moving targets results in distorted beam pattern and signal self-cancelling. In theory, the impact of heterogeneity could be mitigated by DDD approach. However, traditional DDD STAP suffers from an aperture loss and a limitation in array configuration. A novel DDD STAP based on iterative adaptive approach(IAA) is proposed in this dissertation. The proposed approach can avoid the trouble that statistical STAP usually encountered in heterogeneous environment. The other advantages of the proposed method over traditional DDD STAP include no aperture loss and no limitation in array configuration.3. The problem of clutter suppression in the dense deceptive jamming circumstance for airborne radar is studed(A special case of heterogeneous environment). The deceptive sidelobe jamming of airborne radar can easily cause a large amount of false alarms and make the data processor reach saturation point. While the deceptive mainlobe jamming not only causes a large amount of false alarms but also contaminates training samples of the space-time adaptive processor. As a result, the performance on clutter suppression is degraded and signal self-cancellation occurs due to the distorted adaptive pattern. A polarization-space adaptive beamforming algorithm utilizing the polarization difference or angle of arrival difference between the target signal and jamming is proposed for suppressing the deceptive mainlobe or sidelobe jamming. Fistly, utilising the increased auxiliary polarization channels, the polarization-space adaptive beamforming is carried out via synthesizing subarrays with overlapped window. Then, the STAP is utilized to suppress the residual clutter. The proposed method can efficiently suppress the dense deceptive jamming, and hence, reduce the number of false alarms and coumputation load of the radar data processor. The performance of STAP for clutter suppression can also be improved.4. The problem of clutter suppression for short-range ground moving target indication(GMTI) in forward looking airborne radar(FLAR) is considered. The short-range clutter of FLAR is range-dependent. The range dependency will degrade the performance of clutter suppression obtained by STAP. The ambiguous long-range clutter would induce additional blind velocities when the radar system employs mid pulse repetition frequency(MPRF) for detection of short-range target. Spectrum compensation based STAP methods could be used to deal with range-dependent short-range clutter, but the impact of ambiguous far-range clutter is ignored in these algorithms. To eliminate the impact of far-range clutter on target detection, an efficient beamspace-based prefiltering method in elevation is proposed in this dessertation to suppress ambiguous far-range clutter. The proposed elevation beamformer can provide excellent performance on far-range clutter suppression and simultaneously the short-range moving target can be protected. The proposed method can not only eliminate the additional blind velocity, but also significantly improve the clutter suppression performance of azimuth-Doppler STAP. In addition, the proposed beamspace-based adaptive beamforming method not only improves the convergence speed, but also significantly reduces the computational load. Therefore, it is suitable for engineering application.5. The problem of estimation of target’s direction of arrival(DOA) for monostatic MIMO radar is considered. For conventional DOA estimation methods, performance degradation occurs in the low signal-to-noise ratio(SNR) and small samples case. A novel DOA estimation method called reduced-dimensional unitary ESPRIT is proposed in this dissertation. Firstly, the received data is transformed into a low dimensional signal space via the reduced-dimensional transformation. Then, the real-valued rotational invariance equations for the low dimensional signal subspace are constructed to estimate DOAs. The proposed algorithm can provide increased DOA estimation accuracy and reduced computational complexity compared with the conventional ESPRIT algorithms in the low SNR and small samples circumstance.