论文信息 - Processing for continuous radar waveforms

Processing for continuous radar waveforms

Signal processing methods for high resolution pulse compression have been developed based on deconvolution or inverse filtering in the time domain. The pulse compression is formulated using matrix-vector algebra to get inverse filtering with high resolution, low sidelobes and possibly super resolution. These methods have been adapted to processing of non-repeating continuous waveforms. The processing time interval defines a repetition interval for sampling the signals for further processing.

A. Nelander

[1] K. Gerlach,et al. Adaptive pulse compression , 2004, Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509).

[2] J. J. Burlingame,et al. Poly-phase codes and optimal filters for multiple user ranging , 1995 .

[3] Shannon D. Blunt,et al. A novel pulse compression scheme based on minimum mean-square error reiteration [radar signal processing] , 2003, 2003 Proceedings of the International Conference on Radar (IEEE Cat. No.03EX695).

[4] A. Nelander. Analysis of terrain scattered interference-mitigation , 2004, Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509).

[5] W. D. Wirth. High-range resolution for radar by oversampling and LMS pulse compression , 1999 .

[6] Anders Nelander. Deconvolution approach to terrain scattered interference mitigation , 2002, Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322).

[7] T. K. Sarkar,et al. An ultra-low sidelobe pulse compression technique for high performance radar systems , 1997 .

[8] Young Sik Kim,et al. Estimation theoretic approach for radar pulse compression processing and its optimal codes , 2000 .

[9] S. Liu,et al. Novel method for super-resolution in radar range domain , 1999 .