Research On Multichannel Ground Moving Target Indicator Radar With Robust Array Processing

This dissertation addresses the robust array processing techniques in the multichannel ground moving targets indicator (GMTI) radars. Firstly, some robust array processing techniques have been studied. Secondly, some mutual and key techniques in robust array processing are applied in the multichannel GMTI radars to improve the performance of detecting the ground moving targets. The main topics of this dissertation are listed as follows:1. Aimming at the problem of how to choose the diagonal loading (DL) level used in the adaptive beamforming methods of diagonal loading, a new method for estimating the appropriate diagonal loading level is proposed based on the weighted cost function of subspace projection. Without the evalution of system error, the appropriate diagonal level can be rapidly and uniquely obtained through an iterative search which is not sensitive to the given initial valve. Simulations demonstrate the robustness under the variation of output signal-to-noise ration (OSNR) to input signal-to-noise ration (ISNR), look direction error and gains and phases error with our method.2. Aimming at the performance degration of the adaptive beamformer caused by the array manifold error, a new robust beamforming method is proposed for estimating the artificial interference power under the sidelobe soft constraint. Firstly, the robustness of linear constraint minimum variance (LCMV) beamformer is improved by the projection of the steering vector of the signal of interest (SOI) into the signal subspace and the extension technique of the interferences area with the imprecise knowledge of direction of arrival (DOA). Secondly, the artificial interference power can be estimated through the iterative procedure under the soft constraint of the maximum peak undulation in sidelobe area, which is used to satify the requirement of null depth and sidelobe level. Numerical examples demonstrate it has a higher performance of output signal-to-interference-plus-noise ration (OSINR) than Traditional Diagonal Loading (TDL), Covariance Matrix Taper (CMT) and Robust Capon beamformer (RCB) under the same error conditions.3. An optimized method for the phase centres of subarray based on the symmetric exponentially distribution and an ununiform window of subarray are proposed to realize the subarray multibeam-forming and avoid the grating lobe due to the uniform sparse phase centers of subarray. Firstly, given the aperture and the number of the array, the phase centers of the subarray are optimized through an approach of choosing the approatiate exponential parameter. Secondly, an ununiform Taylor window is derived for the sidelobe control according to the optimized phase centers. Finally, the subarray multibeam-forming can be achieved with the windowed steering vector pointing at the various directions. Simulation results show that the linear array with the optimized phase centers and the ununiform window has the advantages of no grating lobe, low sidelobe level nearby the mainlobe and the high array efficiency over other methods; The pattern results of our method applied in the linear array composed of symmetric array elements agree with that of Numerical Electromagnetic Code (NEC) software; The proposed method spreading to the plane array of symmetric exponentially distribution is available.4. For the problems of the clutter data obtained by the multichannel GMTI radar system, such as heterogeneity, insufficiency or weakness and contamination due to the strong moving targets or the isolated interferences, a new method for estimating the spatial steering vectors is proposed. Firstly, the spatial steering vectors are accomplished by two stages of phase and amplitude estimation. Secondly, the suitable clutter data, which are picked out by the beamforming mode with the estimated steering vectors, are used to estimate the adaptive weight for clutter rejection. Thirdly, the moving targets are detected with the results of clutter suppression. Finally, the locations and the radial velocities are estimated by matching the estimated steering vector and the data vector of moving targets. The results of the airborne measured data demonstrate that the jump points in the phase estimation and the bad points in the amplitude estimation can be eliminated; the sample selection method using beamforming has better detection performance than that using power order; the moving targets can be relocated to the road using the match method.5. A robust method for estimating the covariance matrix using the weighted pixels vector for the joint clutter rejection is proposed. Firstly, the pixels vector is weighted by the relative range of the generalized inner product. Secondly, the locations of the ground moving targets are detected using the map of joint clutter rejection with three SAR images. Thirdly, the true locations and velocities of the targets can be obtained by the local interferometric method. Finally, the performance analysis is given. Without the threshold of the sample select and only one pixel image registration being required, the improved factor (IF) of the weighted processing has been improved much more than that of the noweighted processing and the IF of the jointed processing is better than that of the paired processing. The effectiveness and robustness of the proposed method are verified with the process results of measured airborne data.