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机载阵列雷达DBF算法研析.pdf


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机载阵列雷达DBF算法研究ii Abstract Adaptive digital beamforming (ADBF) technique can greatly improve the capability of interference suppress. It’s a key technique to improve target detective performance of modern radar. The application of ADBF is limited by the high cost of transmit/receive (T/R) modules. Over the recent years, the rapid progression in digital hardware and signal processing capabilities stimulates the development of phased array radar systems. The tendency is to move the digital interface toward the antenna, replacing, whenever possible, analog RF-hardware. Based on software codes, these digital systems are more flexible and easier to reconfigure than RF-hardware. Our research es from a project of airborne radar line array antenna’s ADBF system. Firstly,this dissertation introduced the basic of linear array ADBF. And some mainly performance parameters when ADBF technology is applied in radar system are described. Two realizable ADBF algorithms, the sample matrix inversion (SMI) algorithm and DOA estimation algorithm based on MUSIC method, are presented. Simulations have been used to investigate their principle capabilities, limitations and performance parameters. This dissertation is focused on the application of ADBF. In order to control the sidelobe altitude of the adaptive pattern and to realize the ultra-low sidelobe performance of the array system, weighted steering vector and adaptive channel equalization technology are applied. Besides,some methods to resist the jamming are discussed. Finally, this dissertation introduced the parallel process system based on the most popular DSP ADSP-TS201 TigerSHARC. The flowchart of system design is given. And performance analysis plexity are presented for this design. Assembly language programming and optimization are described in detail. Key Words: adaptive digital beamforming (ADBF); DOA estimation; ultra-low sidelobe; adaptive channel equalization; ADSP-TS201 南京航空航天大学硕士学位论文v 相控阵雷达的基本组成图...............

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  • 页数66
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  • 上传人cxmckate1
  • 文件大小701 KB
  • 时间2016-10-24