Study On Joint DOD-DOA Estimation Methods In MIMO Radar Based On Large Dimensional Random Matrix Theory

MIMO (Multiple Input Multiple Output) radar, as a new kind of radar imergingin recent years, has gained a lot of attention due to the tremendous advantages intarget detection and localization. Target parameter estimation is the main content inMIMO radar signal processing, which is also the key to obtain accurate targetlocalization and imaging.In target parameter estimation field, many methods have been proposed on jointDOD-DOA estimation in bistatic MIMO radar. However, those methods of jointDOD-DOA estimation depend on the assumption conditions: the snapshots number ismuch larger than the number of transmitting array elements and receiving arrayelements. Traditional parameter estimation methods use the sample covariance matrixinstead of the statistical covariance matrix. This signal processing means is no longerapplicable when the number of samples and array elements are in the same order ofmagnitude. In addition, since the observation noise distribution in MIMO radar maybe non-Gaussian characteristic, the signal processing methods under Gaussian noiseassumption are no longer applicable. Based on traditional target parameter estimationalgorithms in MIMO radar, the connection between random matrix theory and targetparameter estimation is set up in this thesis. Further, the joint DOD-DOA estimationproblem is investigated in large array MIMO radar.The work of this thesis is supported by the National Natural Science FundationProject of "Robust target detection and estimation for MIMO radar based on largedimensional random matrix theory"(No:61371158). The main innovation work inthis thesis is as follows:For the condition that the snapshots number is limit, the Gaussian random matrixmodel of echo data in bistatic MIMO radar is built. On this basis,2D-GMUSICalgorithm is proposed, which is a joint DOD-DOA estimation method based on largedimensional random matrix theory. It can estimate the target parameters on thecondition that the number of the snapshots and the sensor array elements arecomparable. Then, a2D-G-SSMUSIC method is proposed, which can improve theperformance of target estimation. Using the methods above, the target parameters can only be estimated underGaussian noise background assumption. Based on robust estimate and random matrixtheory, two methods named Robust-2D-GMUSIC and Robust-2D-G-SSMUSIC arefurther proposed in this thesis. These algorithms can achieve joint DOD-DOAestimation in MIMO radar under the condition of non-Gaussian noise.In order to avoid spectral peak search in the Robust-2D-GMUSIC method, aRobust-2D-ROOT-GMUSIC method is put forward, which is based on random matrixtheory and polynomial rooting technique. This method can realize time saving andautomatic pairing. Due to utilizing polynomial rooting technique, it can realize similaror identical DOAestimation accurately.