Space-time Adaptive Processing And Moving Target Indication

Space Time Adaptive Processing(STAP)can effectively improve the performance of ground clutter suppression in airborne phased array radar. This technique has been gradually applied to airborne radar for air moving targets indication (AMTI) and ground moving targets indication (GMTI), especially for airborne early warning (AEW) radar.The ground clutter has to be suppressed effectively before moving target indication. Due to the motion of airborne platform, the ground clutter spectra for airborne phased array radar are distributed in space-time domain. But the traditional one-dimensional filter can not form a notch that matches for the ground clutter, so it can not suppress clutter effectively. However, Space Time Adaptive Processing is a two-dimensional filter in space-time domain, whose weight is calculated by maximum SCNR criterion,so it can suppress ground clutter perfectly. Therefore, STAP becomes a key technique in airborne phased array radar for clutter suppression.Focusing on the engineering techniques for STAP applying to airborne phased array radar and the related problems of airborne radar for MTI, the dissertation presents and improves some signal processing algorithms. The main contents of the dissertation are described as following.1. Chapter 2 specifically analyzes the relationship between the clutter distribution of AEW radar and its radar system parameters, and finds out the causation of clutter range dependence. The range dependence of short-range clutter is the key factor affecting clutter suppression and MTI. Since the clutter distribution law for airborne non-side-looking array radar has been fully researched, we propose two approaches to mitigating the effect of short-range clutter. The first one is called elevation filtering approach, i.e. the short-range clutter is suppressed by utilizing the elevation elements of array antenna. The weight for elevation filtering is calculated nonadaptively. The second one is named elimination approach, i.e. the clutter range-Doppler distribution is firstly calculated in accordance with radar system parameters, and the range cells, including the short-range clutter, are eliminated before estimating covariance matrix. By doing so, the effect of training data pollution in STAP is mitigated. Both approaches are realized nonadaptively, and they can achieve good performance when the system error is negligible.2. Chapter 3 improves the elevation filtering approach, and presents an approach to the calculation of the elevation weight adaptively. This dissertation proposes two ways of training data strategies: in the first way, the training data is selected from the Doppler domain in the clutter support area, while in the second one, the training data is directly selected in the pulse domain. The performance of elevation filtering approach and 3-D STAP are compared, and the simulation experiment testifies that the elevation filtering STAP is superior to 3-D STAP in both performance and computational load.3. The reduced-dimension STAP related to overlapped-subarray synthesis is studied in Chapter 4. The dissertation contributes to this study by improving the sliding overlapped-subarray synthesis. The planar subarray synthesis and the subarray synthesis with reserved auxiliary column-subarray are presented in this dissertation. For the subarray synthesis with reserved auxiliary column-subarray, a cascaded approach in which the interference and clutter are suppressed respectively is proposed. First, the interference is suppressed adaptively by utilizing one main subarray and all the auxiliary column-subarrays, and then the clutter is suppressed by STAP. The dimension for STAP can be reduced at the same time as interference suppression, and the simulation experiment testifies that with the same spatial DOF, the performance of this cascaded algorithm approaches the performance of STAP in which interference and clutter are suppressed simultaneously. However, the computational load is reduced greatly.4. Chapter 5 studies the STAP application to bistatic airborne radar. This dissertation specifically analyzes the relationship between the bistatic clutter distribution and the bistatic geometry, and then deduces a formula for calculating the bistatic clutter distribution. Moreover, we find out several change laws of bistatic clutter spectra. In the author's opinion, the range dependence of bistatic clutter has to be mitigated before STAP technique can be applied to bistatic airborne radar, therefore, we suggest that the clutter range ambiguity should be resolved by utilizing spatial DOF (degrees of freedom) firstly, and then the clutter range dependence is compensated in angle-Doppler domain. This approach effectively solves the problem of bistatic clutter range dependence in the case of range ambiguity, so it is of great help for STAP applying to bistatic airborne radar.5. Chapter 6 mainly studies the coherence of SAR image pairs. The coherence of SAR image pairs affects the performance of GMTI directly. There are many factors affecting the coherence of SAR image pairs, but this dissertation mainly focuses on the effect of baseline and ground slope. In accordance with SAR imaging principle, we study the relationship between coherence coefficient and baseline numerically. The presented formula for coherence coefficient calculation is of significance to baseline designing for SAR-GMTI.