Study On Parameters Estimation Of MIMO Radar

By emitting arbitrary waveforms (usually noncorrelated or orthogonal) via each transmit sensor and exploiting a matched filterbank to extract these waveforms from the reflected signals to achieve flexibility of processing and improved performance, multiple-input multiple-output (MIMO) radar has been a hot research topic. To date MIMO radar can be classified as two broad kinds. The first kind is small-scaled coherent MIMO radar, of which the antennas are closely spaced (so-called small-scaled) and therefore both the direction-of-arrival (DOA) and direction-of-departure (DOD) are identical for all the re-ceive sensors and all the transmit ones, respectively. It has potential advantages over its counterpart (the traditional phased radar), such as increased degree-of-freedoms (DOFs), extended target identification and improved performance of parameters estimation and so on. The other kind is large-scaled noncoherent MIMO radar with widely separated antennas, namely large-scaled array. Since different antennas detect different aspects of targets, it can provide transmit/receive spatial diversity and improve the detection per-formance of target scintillations, especially in the case that signal-to-noise ratio (SNR) is relatively high. This dissertation mainly studies parameters estimation of the coherent MIMO radar, and they are concluded as follows:1. Around the idea that parameters estimation performance of MIMO radar can be improved by exploiting the transmit array aperture DOFs, the principle of MIMO radar is studied. In colocated MIMO radar, there are redundant terms in the array manifold. Furthermore, owing to the incorporation of the transmit DOFs in receive site, the computational complexity is high. To alleviate the computational complex-ity problem, two algorithms are proposed. The first one is reduced-dimensional ESPRIT-like algorithm with improved estimation accuracy of angle and Doppler frequency, in which both angle searches and phase unwrapping can be avoided. The other algorithm is the 2D-FFT based reduced-dimensional angle-Doppler esti-mation algorithm. In this algorithm, the received signal matrix of each receiver is first partitioned into four blocks. Then 2D-FFT is applied to each block in order to achieve coherent integration. By utilizing the data corresponding to the peaks of co-herent integration in each block, a reduced-dimensional data vector is constructed for angle and Doppler frequency estimation. Since the full-dimensional covariance matrix estimation and eigendecomposition are avoided, the computational cost of the presented algorithm is relatively low. The superiority is much more notable for either large array or large number of snapshots. 2. Joint DOD and DOA estimation algorithms at the receive site are presented for bistatic MIMO radar, such as ESPRIT-like algorithms by means of rotational factor via either the transmit array or the receive array, combined MUSIC with ESPRIT algorithm for angle estimation by utilizing multi-antenna transmit and two-antenna receive, and the reduced-dimensional direction finding approach, which are uti-lized to implement multi-dimensional parameters estimation with low complexity. By employing MUSIC with single-sensor owing to its utilization of transmit ar-ray aperture and ESPRIT with two-sensor via the rational invariance property of the signal-subspace at the receive end, the DODs and DOAs of the targets can be estimated separately and paired automatically. Two-order moment and four-order cumulant based MUSIC-ESPRIT are suggested for the spatial Gaussian white noise and the colored noise, respectively.3. MIMO array error calibration and robust MIMO array signal processing which se-riously influence the application of high-performance array techniques are studied. Aiming at the DOA-independent gain-phase error, an algorithm for multitarget joint angle and gain-phase error estimation for bistatic MIMO radar is proposed. Both the transmit array manifold and receive array manifold involving the gain-phase er-rors are obtained by joint-diagonalization. Then by minimizing the mean square of phase error for transmitter and receiver respectively, the DODs and DOAs of targets can be estimated. Finally, combined with the obtained angles, the closed-form so-lution of the gain-phase error can be solved by the gain-phase error self-calibration algorithm. With no need for the prior knowledge of the gain-phase error, the pro-posed method is much more robust. In the presence of mutual coupling, an algo-rithm for mutual coupling self-calibration is given. Based on the special structure of the coupling matrix of uniform linear array (ULA), the angles can be estimated directly by double one-dimensional searches without the knowledge of the mutual coupling matrices. Then the mutual coupling coefficients of the transmit array and the receive array can be solved in closed-form by utilizing the obtained DODs and DOAs, respectively.4. Since parameters estimation performance degrades seriously owing to the presence of the Doppler-extended clutter in airborne MIMO radar, an algorithm for joint DOA and Doppler frequency estimation based on the maximum likelihood principle is studied. However, it is computationally expensive as it requires two-dimensional searches. Three methods are introduced to reduce its computational complexity, in-cluding the alternative algorithm for DOA and Doppler frequency estimation, joint estimation of DOA and Doppler frequency based on 2D-FFT and the space-time adaptive monopulse approach.