脉冲压缩
计算机科学
雷达
滤波器(信号处理)
校准
逐渐变细
数据压缩
压缩(物理)
电信
算法
数学
材料科学
计算机视觉
计算机图形学(图像)
复合材料
统计
作者
Cesar M. Salazar,Boon Leng Cheong,Robert D. Palmer,David Schvartzman,Alexander V. Ryzhkov
出处
期刊:IEEE Transactions on Geoscience and Remote Sensing
[Institute of Electrical and Electronics Engineers]
日期:2024-01-01
卷期号:62: 1-14
标识
DOI:10.1109/tgrs.2024.3353174
摘要
Progressive Pulse Compression (PPC) was introduced to mitigate the need for a fill pulse in pulse-compression-based radar systems. It provides a method for recovering signals in the blind-range region created by the transmission of relatively long pulses. However, the initial implementation of PPC has limitations that need to be addressed for it to be more useful for meteorological applications. The proposed updated algorithm, named herein PPC+, brings significant improvements to mitigate these limitations. The methodology of PPC+ is similar to that of PPC, except that it uses a set of improved pulse compression filters. The improved compression filters are designed based on an amplitude modulation approach and are generated by multiplying the original filter by a range-dependent window. The window can be divided into two sections, the first part has a number of nulled samples used for mitigating the mainlobe migration, and the remaining portion is a number of tapered samples to alleviate the “shoulder” effect from range sidelobes. Also, in contrast to PPC, the calibration factor used in PPC+ is further tuned to account for the tapering used in the improved compression filters. The PPC+ technique has been tested using data collected with PX-1000, a polarimetric X-band transportable solid-state radar system designed and operated by the Advanced Radar Research Center (ARRC) at the University of Oklahoma, and it is implemented and operational on that system (data available at https://radarhub.arrc.ou.edu). This technique has also been implemented on Horus, a fully digital phased array radar recently completed at the ARRC.
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