Research And Application Of Parallel Processing Technology In Radar Signal Processing

The massive processing volume of large scale scientific computation and high speed real-time signal processing should be realized by parallel processing technology instead of the conventional single-processing systems with limited processing capability. Among the applications needing massive processing, the advanced radar signal processing systems with powerful function and complicated construction and sophisticated processing manner need fast response, high data precision, wide dynamic range and very high data throughput besides the processing speed of billion to tens of billion floating-point operations per second. The paper is mainly on the question of design and construct real-time parallel processing system used in radar signal processing, and is responsible of proposing schemes of the realization of two kinds of application in this region. To design a parallel processor means much synthesis work in algorithm research, VLSI design, system configuration and network topology. In Chapter 2, the author begins with establishing a timing model reflecting the performance of parallel processor, with this model, the three main factor having important influence on the performance are displayed: the processing element, the configuration of network, the parallel algorithm and task allocation method. We can see that the general purpose DSP are the best choice of processing element for radar signal processing, the distributed system and shared-bus system will present different performance in differed processing dimension. And we prefer one kind of task allocation method than the other depending on the characteristic of task. In Chapter 3, a statistics of computation and communication burden on the main kinds of radar signal processing is given, a method of realizing linear convolution of time domain in the frequency domain is proposed. All these prove that the general purpose DSP is capable of processing all kinds of radar signal processing. Then the author designs several kinds of parallel processing module which can be used in a wide area of real-time processing. The bottleneck of radar signal processing is matrix decomposition which is more complicated. In Chapter 4, A detailed comparison between the realization of Cholesky decomposition and OR method is given, a systolic/wavefront array made of general purpose DSP is used to realize the adaptive beamforming at a moderate speed, and a wavefront array to extract the adaptive weights which is necessary in some applications is designed. In Chapter 5, the author proposed a new structure to realize the space time adaptive processing. First 1~q using the FFr and the truncating infinite sequence and sone optimizing method, a much simpler architecture can be acquired in realizing the three portion of channel processing: quadrature sampling, pulse compression and adaptive equalization. Then proposed several methods in adaptive beamforming and analyze their performance, complexity and speed under different data sampling speed, channel number and adaptive requirement. Aiming at the actual in-progress system designing, one method is applied using the unified type of parallel processing module. To decrease the hardware ccm~lexity, the author optimizes the network connection and data conununication scheme. So a STAP parallel processor with much less equipaent, higher performance and high degree generalization is acquired. In order to realize the real-time Inverse Sy...