Study On Parameter Estimation Technology For MIMO Radar

As a new radar system, Multiple-Input Multiple-Output (MIMO) radar is becomingpopular in radar field since its unique advantages compared with the phased array radar.MIMO radar transmits multiple orthogonal transmitted waveforms and receivesreflected signals with multiple received arrays, which can form many channels betweentransmitting and receiving array, and can achieve flexible transmitting diversity design.In contrast with the conventional phased array radar, MIMO radar provides a noveltechnique for increasing the degrees of freedom of the radar system and improving theperformance of detection and parameter estimation. This dissertation mainly focuses onthe parameter estimation of MIMO radar. The main content of this dissertation issummarized as follows:1. The method for angle estimation of coherent sources in bistatic MMO radar isresearched. Firstly, based on the existed DOA matrix method, a method for angleestimation of coherent sources based on dimension reduction DOA matrix in thepresence of spatially white Gauss noise is presented. The virtual array date ofmultitarget echoes in MIMO radar receivers is uncorrelated utilizing the virtualsubarrays formed by MIMO radar, and the DOA matrices are constructed. Thedimension reduction DOA matrices which reduce the computational complex areobtained by the relationship between signal subspace and DOA matrices, and the jointestimation of DOD and DOA can be obtained by the corresponding relationshipsbetween the eigenvalue or eigenvector and the estimated parameters. Secondly, thedimension reduction DOA matrix method in spatially white noise circumstance isextended to the spatially colored noise circumstance. The spatially colored noise iseliminated by using the orthogonality of the transmitted signals of MIMO radar, and thejoint estimation of DOD and DOA can be obtained by using dimension reduction DOAmatrix method. The proposed methods do not need the multi-dimensional peak search,and can estimate the parameters of coherent sources without pairing in both two noisecircumstances. Moreover, it is applicable to receiving arrays without an invariancestructure.2. The method of joint estimation of angle and Doppler frequency for bistaticMIMO radar in spatial colored noise is researched. According to the characteristic of thesignal model of bistatic MIMO radar, the spatial colored noise can be eliminated byusing the cross-correlation of the match filter outputs in different time delay sampling.Firstly, a method of joint estimation of angle and Doppler frequency for bistatic MIMO radar in spatial colored noise based on simultaneously singular value decomposition isproposed. Utilizing the cross-correlation matrix which is formed by the adjacent outputsof match filters in the time domain, a new matrix is constructed to eliminate theinfluence of spatial colored noise, and the signal subspace is obtained from singularvalue decomposition (SVD) of it. Then angles and Doppler frequencies can beestimated based on ESPRIT using the rotational factor produced by adjacent outputs ofmatch filters. Secondly, a method of joint estimation of angle and Doppler frequency forbistatic MIMO radar in spatial colored noise based on dimension reduction DOA matrixis proposed. This method utilizing the temporal information to construct the temporalrotational factor, and angles and Doppler frequencies is obtained by using dimensionreduction DOA matrix. In the proposed tow methods, the spatial colored noise can beeliminated, and the angles and Doppler frequencies can be obtained simultaneously andautomatically paired without array aperture loss. Besides, the proposed methods can beextended to the circumstance of spatially and temporally colored noise, and can be usedfor angle estimation of conventional array in the presence of colored noise. The CRB ofthe angle and Doppler frequency of bistatic MIMO radar based on spatial-temporalstructure is proposed.3. The DOA matrix method based on MIMO radar with L-shape arrays isresearched. Firstly, a two-dimension (2-D) angle estimation method for multiple inputmultiple output (MIMO) radar with L-shape arrays based on direction of arrival (DOA)matrix is proposed. This method divides the2-D virtual plane array which is generatedby MIMO radar into two overlapping subarrays, and constructs an estimation matrix toestimate the2-D angles. To solve the problem of angle annexation, a jointdiagonalization DOA matrix method is proposed later. This method generates foursubarrays from the2-D virtual plane array, and uses the joint diagonalization algorithmto estimate the2-D angles. The proposed method secures the advantages of the existingDOA matrix method such as no requirement of2-D angle search and autopairing ofparameters, avoids the angle annexation problem, reduces the loss of the array aperture,and improves the performance of the angle estimation effectively.4. Low-angle estimation in VHF radar is researched. The effect of the existedlinear preprocessing method to the noise structure is analyzed. Aimed at thedisadvantage that the linear preprocessing method changed the white noise of the realarray data to correlated noise which reduces the performance of angle estimation in lowSNR, an improved linear preprocessing method is proposed. This method greatlyimproved the performance of the low-angle estimation through the whitened processing of the data after linear preprocessing without increasing the computational burdensignificantly. To reduce the computational burden of the linear preprocessing method, afast algorithm of linear preprocessing based on propagator method is proposed. Thisalgorithm replaces the eigendecomposition of the cross-correlation matrix with linearoperation in each searching angle, and greatly reduces the computational burden.Moreover, the performance of the proposed algorithm is much better than theconventional linear preprocessing method, and is identical with the improved linearpreprocessing method due to the whitened processing.6. Low-angle estimation in VHF MIMO radar is researched. Firstly, the multipathsignal model for MIMO radar is constructed with both transmitted multipath andreceived multipath signals being considered. Secondly, a twice differentialpreprocessing method for low-angle estimation in VHF MIMO radar is proposed. Withtwice differencing preprocessing of the received echoes of the VHF MIMO radar, thetransmitted multipath signals and received multipath signals are eliminated, and theconventional MUSIC algorithm can be used to obtain the estimation of low-angle. Theproposed method can overcome multipath effect and estimate the low-angle of the targeteffectively, and is not sensitive to the signals environments.