Spectral Analysis Method to Eliminate Spurious in FMICW HRR Millimeter-Wave Seeker

Abstract

In this thesis, we develop a spectral analysis scheme to eliminate the spurious peaks generated in HRR Millimeterwave Seeker based on FMICW system. In contrast to FMCW system, FMICW system generates spurious peaks in the spectrum of its IF signal, caused by the periodic discontinuity of the signal. These peaks make the accuracy of the system depend on the previously estimated range if a band pass filter is utilized to eliminate them and noise floor go to high level if random interrupted sequence is utilized and in case of using staggering process, we must transmit several waveforms to obtain overlapped information. Using the spectral analysis one of the schemes such as IAA(Iterative Adaptive Approach) and SPICE(SemiParametric Iterative Covariance-based Estimation method) which were introduced recently, the spurious peaks can be eliminated effectively. In order to utilize IAA and SPICE, since we must distinguish between reliable data and unreliable data and only use reliable data, STFT(Short Time Fourier Transform) is applied to the distinguishment process.

Multi-Target Detection in FMICW Radar Using Machine Learning

“…FMICW 레이다에서 스퓨리어스 신호 제거용 대역통과 필터(BPF)를 사용하여 스퓨리어스가 없는 영역만 처리하 는 방식은 사용할 수 있는 주파수를 크게 제한시키는 단 점을 가지고 있다 [3] . 대역통과필터를 적용하여 사용 주파 수를 제한하는 FMICW와 일반적인 FMCW 신호 처리는 유사하게 이루어지며, 허상 표적(ghost target)을 제거하기 위해 서로 다른 세 개 이상의 chirp 주파수를 사용하여 거 리와 속도를 추정한다 [4] .…”