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Analysis of the channel estimate model in passive radar using OFDM waveforms.

Authors :
Lyu, Xiaoyong
Liu, Baojin
Fan, Wenbing
Quan, Zhi
Source :
Digital Signal Processing. Feb2024, Vol. 145, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

The paper takes an in-depth analysis of the channel estimate model (CEM) in passive radar using the orthogonal frequency division multiplexing (OFDM) waveforms. The CEM has been intensively exploited in OFDM passive radar, where the channel estimates (CE) are obtained from the original digitized received signal (ODRS), and target detection is performed based on CEs. However, traditional CEM is derived neglecting the inter-carriers interference (ICI). The influence of the ICI on target detection has rarely been discussed previously. In fact, target with large power and Doppler frequency can induce strong ICI, which increases the noise floor, and thus imposes significant influence on the detection of the other targets, especially the weak targets. In this paper, we rederive the CEM taking the ICI into consideration, and obtain a new CEM. In the new CEM, a specific target has two components, i.e., the useful signal part, and ICI. We derive the useful signal to noise ratio (SNR) and ICI to noise ratio (ICINR) theoretically, and provide compact expressions. We reveal the relationship between the SNR and ICINR in the CE, and the SNR in the ODRS. Based on the theoretical derivation, the influence of ICI is analysed. We also discuss the elimination of the ICI. The influence of ICI can be eliminated by cancelling the target signal that induces the ICI from the CEM. A target signal cancellation method is developed based on the new CEM. Simulations demonstrate the effectiveness of the theoretical analysis of the CEM and the proposed cancellation method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10512004
Volume :
145
Database :
Academic Search Index
Journal :
Digital Signal Processing
Publication Type :
Periodical
Accession number :
174642844
Full Text :
https://doi.org/10.1016/j.dsp.2023.104303