Spectral analysis of nonuniformly sampled data using a least square method for application in multiple PRI system

Jinhwan Koh, Tapan Kumar Sarkar

Research output: Chapter in Book/Entry/PoemConference contribution

5 Scopus citations

Abstract

This paper addresses the problem of spectrum analysis from nonuniformly sampled data using the least square method for applications in multiple PRF radar system. The benefits of using a direct spectrum analysis using nonuniformly spaced data instead of using a FFT based CR(Chinese Remainder) theorem has been presented. Using a spectrum analysis based on nonuniformly spaced data, the blind bursts that the target frequency is folded into the clutter band could be overcome easily. Additional benefits of using an unevenly spaced data spectrum is its robustness to noise. It is shown that the least square method outperforms conventional Chinese remainder theorem based on FFT method by 2.5[dB] of SNR. This can also be an efficient method when there exist multiple interferences with same magnitude as the target. To obtain a spectrum from nonuniformly sampled data, the well known Lomb periodogram has been modified to fit a complex sequence. Phase component has also been recovered from the power representation to determine whether the target is opening or closing. The result of a modified scheme is compared to the result of the Lomb periodogram.

Original languageEnglish (US)
Title of host publicationIEEE International Symposium on Phased Array Systems and Technology
PublisherIEEE Computer Society
Pages141-144
Number of pages4
StatePublished - 2000
Event2000 IEEE International Conference on Phased Array Systems and Technology - Dana Point, CA, USA
Duration: May 21 2000May 25 2000

Other

Other2000 IEEE International Conference on Phased Array Systems and Technology
CityDana Point, CA, USA
Period5/21/005/25/00

ASJC Scopus subject areas

  • General Engineering

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