Loading [MathJax]/extensions/MathMenu.js
Performance Prediction of the Loaded Reciprocal Filter for OFDM-based Passive Radar | IEEE Conference Publication | IEEE Xplore

Performance Prediction of the Loaded Reciprocal Filter for OFDM-based Passive Radar


Abstract:

The Range-Doppler maps of Passive Bistatic Radar (PBR) are often evaluated by means of the suboptimal batches algorithm. For OFDM waveforms of opportunity, the Reciprocal...Show More

Abstract:

The Range-Doppler maps of Passive Bistatic Radar (PBR) are often evaluated by means of the suboptimal batches algorithm. For OFDM waveforms of opportunity, the Reciprocal Filter (RF) is often used to perform range compression at each batch since it provides a high Peak-to-Sidelobe Ratio (PSLR) while suffering from relatively low Signal-to-Noise Ratio (SNR) losses when the signal is fragmented in batches equal to the OFDM symbols. In some applications, this fragmentation leads to a performance degradation and an unconstrained batching strategy should be use. For this fragmentations, the RF keeps a high PSLR but yields significant SNR losses. To solve this issue, the Loaded Reciprocal Filter (LRF) has been proposed as an empirical modified RF version that provides a trade-off between SNR losses and PSLR. In this paper, we extend our previous results and provide a theoretical analysis of the performance of the LRF.
Date of Conference: 28-30 September 2022
Date Added to IEEE Xplore: 25 October 2022
ISBN Information:
Conference Location: Milan, Italy

I. Introduction

Passive bistatic radar (PBR) systems have recently received great interest from the research community. They operate by exploiting an already existing illuminator of opportunity which provides covert operation, low environmental impact, and reduced cost. Among the available illuminators of opportunity those based on an OFDM modulation represent an attractive choice for their wide availability [1][2]. Therefore, this paper will consider specific issues of OFDM-based PBR.

Contact IEEE to Subscribe

References

References is not available for this document.