Passive detection using orthogonal frequency division multiplex signals of opportunity without multipath clutter cancellation

Fang, Liang; Wan, Xianrong; Gao, Fuqing; Cheng, Feng; Ke, Hua

doi:10.1049/iet-rsn.2015.0238

Cited by 10 publications

(4 citation statements)

References 30 publications

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“…The reference signal serves two important purposes. Firstly, it contributes to clutter cancellation to suppress direct waves and clutter in the echo signals [31]. Secondly, it facilitates a coherent accumulation with the echo signals for target detection [32].…”

Section: Introductionmentioning

confidence: 99%

A Segmented Sliding Window Reference Signal Reconstruction Method Based on Fuzzy C-Means

Liang,

Feng,

Zhang

et al. 2024

Remote Sensing

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Reference signal reconstruction serves as a crucial technique for suppressing multipath interference and noise in the reference channel of passive radar. Aiming at the challenge of detecting Low-Slow-Small (LSS) targets using Digital Terrestrial Multimedia Broadcasting (DTMB) signals, this article proposes a novel segmented sliding window reference signal reconstruction method based on Fuzzy C-Means (FCM). By partitioning the reference signals based on the structure of DTMB signal frames, this approach compensates for frequency offset and sample rate deviation individually for each segment. Additionally, FCM clustering is utilized for symbol mapping reconstruction. Both simulation and experimental results show that the proposed method significantly suppresses constellation diagram divergence and phase rotation, increases the adaptive cancellation gain and signal-to-noise ratio (SNR), and in the meantime reduces the computation cost.

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Section: Introductionmentioning

confidence: 99%

A Segmented Sliding Window Reference Signal Reconstruction Method Based on Fuzzy C-Means

Liang,

Feng,

Zhang

et al. 2024

Remote Sensing

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“…Generally, due to a particularity of PBR systems, the reference signal is not subject to the PBR designer. Its specific structure type and inherent autocorrelation feature may lead to unwanted peaks and sidelobes in the ambiguity function (AF) [19,20]. These sidelobes often have a level not much lower than the main peak, which may raise the range-Doppler (RD) pedestal, and thus degrade the detection probability.…”

Section: Introductionmentioning

confidence: 99%

An Inter-Subband Processing Algorithm for Complex Clutter Suppression in Passive Bistatic Radar

et al. 2021

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Clutter suppression is a challenging problem for passive bistatic radar systems, given the complexity of actual clutter scenarios (stationary, time-varying and fractional-order clutter). Such complex clutter induces intense sidelobes in the entire range-Doppler plane and thus degrades target-detection performance, especially for low-observable targets. In this paper, a novel method, denominated as the batch version of the extensive cancellation algorithm (ECA) in the frequency domain (ECA-FB), is presented for the first time, to suppress stationary clutter and its sidelobes. Specifically, in this method, the received signal is first divided into short batches in the frequency domain to coarsen the range resolution, and then the clutter is removed over each batch via ECA. Further, to suppress the time-varying clutter, a Doppler-shifted version of ECA-FB (ECA-FBD) is proposed. Compared with the popular ECA and ECA-B methods, the proposed ECA-FB and ECA-FBD obtained superior complex clutter suppression and slow-moving target detection performance with lower computational complexity. A series of simulation and experimental results are provided to demonstrate the validity of the proposed methods.

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“…The classical approach, denoted here as simultaneous approach, is to perform range and speed processing simultaneously, usually by means of a 2D cross-correlation function (2D-CCF) [1]. However another approach, denoted here as decoupled approach, obtains better results by exploiting the characteristics of OFDM to perform the range processing and the Doppler processing separately [4]. This decoupling also allows to perform range processing with channel estimation techniques from OFDM-based telecommunications, e.g.…”

Section: Introductionmentioning

confidence: 99%

“…The decoupled approach allows to apply clutter removal methods of lower complexity than ECA [4]. With this approach, clutter removal is performed between range and speed processing, in the CR 2 block.…”

Section: Introductionmentioning

confidence: 99%

Clutter removal for Wi-Fi-based passive bistatic radar

Storrer

Yildirim

Desset

et al. 2020

2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)

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We address the problem of static clutter removal in Wi-Fi-based passive bistatic radars. Our goal is to detect slowly moving targets in highly cluttered indoor environments, using Orthogonal Frequency-Division Multiplexing signals from the 802.11n and 802.11ac Wi-Fi standards as sources of opportunity. We propose alternatives to the commonly used Extended Cancellation Algorithm (ECA) clutter removal method. Those alternatives are compared to ECA with simulations using an innovative metric based on CA-CFAR detection, and validated with experimental measurements using two Universal Software Radio Peripherals, along with a fan and an electric train as radar targets. The conclusion of that analysis is that, thanks to the decoupled range and Doppler radar processing, simple novel methods such as Average Removal are efficient alternatives to the computationally intensive ECA which is currently the stateof-the-art in CR.

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Passive detection using orthogonal frequency division multiplex signals of opportunity without multipath clutter cancellation

Cited by 10 publications

References 30 publications

A Segmented Sliding Window Reference Signal Reconstruction Method Based on Fuzzy C-Means

A Segmented Sliding Window Reference Signal Reconstruction Method Based on Fuzzy C-Means

An Inter-Subband Processing Algorithm for Complex Clutter Suppression in Passive Bistatic Radar

Clutter removal for Wi-Fi-based passive bistatic radar

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