Two-dimensional DOA Estimation Algorithm Theory Of Array Signal And Its Application Research

The conventional anti radiation missile (ARM) passive radar seeker (PRS) has the disadvantages including low precision, poor resolution and disability to handle simultaneous signals based on phase interferometer mechanism. This dissertation applys spectral estimation algorithm based on array signal processing to PRS, in order to achieve two-dimensional high-precision, super-resolution, real-time direction of arrival (DOA) estimation. The problems in practices including source number estimation, utility of polarization sensitive array, array geometry designing optimization and fast implementation of spectral estimation algorithm are mainly researched in this thesis.The excellent performance of spectral estimation algorithm is under the assumption of knowing the source number precisely, so the correct estimation of source number is the precondition to achieve precise DOA estimation. Source number estimation methods under different conditions is studied. While the practical system is ideal, source number can be estimated by information theory criteria method with the Gaussian white noise background, or by diagonal loading to the covariance matrix information criteria or Gerschgorin disk theorem with the colored noise background. When the practical system is not ideal, the noise will become spatial colored in respect of the existence of mutual coupling and channel mismatch. To deal with this case, a new method called improving the parameter space of information criteria is proposed. Simulation and experimental measurement results illustrate the effectiveness of the new method.The spectral estimation algorithms represented by multiple signal classification (MUSIC) algorithm have the performance of high-precision and super-resolution. However, in practices, it has been proved that due to the limited snapshots, the existence of mutual coupling and channel mismatch and some other factors, the algorithms perform well with high precision only when dealing with single source, and would result in quite poor resolution when dealing with multiple sources. How to improve the resolution of spectral estimation algorithms to achieve high-resolution performance by using polarization sensitive arrays is proposed and studied. With polarization sensitive array, the spatial and polarizational joint spectrum is defined by using MUSIC algorithm. And the super-resolution performance of the joint spectrum was analysed through theoretical analysis and simulation. Then the joint spectrum estimation based on TLS-ESPRIT algorithm is introduced. Finally, a new algorithm called MUSIC algorithm based on polarization rotation matrix is proposed. This method reduces four-dimensional spectrum search to two-dimensional, which greatly improves the real-time performance while maintains the super-resolution of joint spectrum. The simulation results show the effectiveness of this method.In array signal direction finding, different algorithms lead to different performance of direction of arrival (DOA) estimation. Meanwhile, the array geometry has important impact on the final performance of direction finding algorithm. The precision and resolution performance of different array geometry is studied by array differential geometry, and also array designing method is discussed theoretically. And the rank-1 ambiguity issue which has the most serious effectiveness in direction finding is studied. A sufficient condition of non-existing of rank-1 ambiguity is derived based on arbitrary planar array, which can guide to making full use of array aperture without creating rank-1 ambiguity in practical projects.The spectral estimation algorithm based on array signal processing has excellent performance of high-precision and super-resolution, but it is much more computational complicated than conventional DF mechanism. It needs a large quantity of computation, and as a result, its real-time performance is comparably much poorer. In order to guarantee real-time performance, a design of high-speed DF device based on MUSIC algorithm is developed. The DF device works with an existed experimental PRS platform. It makes use of four ADI' high performance floating point DSPs TS201S in hardware design of the DF device. And the four DSPs combine a parallel digital signal processor by sharing bus and tightly coupling. In software design, a method of computing spectrum by steering vector table search is proposed. And thus the DF device achieves very high speed. The experimental test results about accuracy and real-time performance of the DF device provide a very valuable reference for developing new PRS.