基于压缩感知的长球面波函数微弱GNSS信号采集

Tamesh Halder, A. Bhattacharya
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引用次数: 1

摘要

GNSS信号在到达地面接收机时受到噪声的污染,导致接收机性能较差。为了提高接收机的性能,我们在接收机的采集单元中使用大带宽或高复杂度平台或两者的组合,其中测量码偏和多普勒频率。在任何一种情况下,GNSS信号都可以以高于奈奎斯特频率率的速率有效采样。感兴趣的信号(SOI)占用更小的带宽,通过使用压缩感知(CS),我们推导出信号的稀疏性,并最小化采集所需的采样点。长球面波函数(PSWF)由于在时域和频域同时具有良好的局域性,被用作CS中傅里叶基或小波基的替代品。为了提高GNSS信号的成功采集率,我们在CS框架中使用了稀疏数据的动态分组。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Weak GNSS signal acquisition using prolate spheroid wave function based compressive sensing
GNSS signal is contaminated with noise when it reaches the ground receiver because of which the receiver has poor performance. To enhance the performance of receiver, we use a large bandwidth or high complexity platform or a combination of both in the receiver's acquisition unit, where code-offset and Doppler frequencies are measured. In either case, the GNSS signal can be effectively sampled at a rate higher than the Nyquist frequency rate. The signal of interest (SOI) occupies a much smaller bandwidth and by using Compressive Sensing (CS), we derive the sparsity of the signal and minimize sampling points that are needed for acquisition. Prolate spheroid wave function (PSWF) is used as a replacement for Fourier or wavelet bases in CS as it is well localized both in time and frequency domain simultaneously. We use dynamic grouping of sparse data in the CS framework to achieve a higher successful acquisition rate of GNSS signal.
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