A signal processing scheme for a multichannel passive radar system

Palmer, J.

doi:10.1109/icassp.2015.7179038

Cited by 6 publications

(1 citation statement)

References 8 publications

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“…Exploiting its inherent characteristic of not emitting radio waves, it eliminates the influence of radio interference and effectively avoids being detected and disrupted by enemy [13,14]. Compared with traditional radars, its excellent low-altitude coverage capabilities and easy deployment give it obvious advantages in detecting LSS targets [15,16]. However, the emission power and waveform parameters of illumination sources are uncontrollable [17].…”

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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Range-Doppler Domain-Based DOA Estimation Method for FM-Band Passive Bistatic Radar

Park

Kim

2020

IEEE Access

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Recently, a range-Doppler map-based direction-of-arrival (DOA) estimation method was proposed for amplitude modulation (AM) radio-based passive bistatic radar (PBR). This method estimates the incident angle from the phase difference of the range-Doppler-bin (RD-bin) for the specific bistatic range of the cross-ambiguity function (CAF) and the Doppler frequency value rather than the phase difference between each antenna signal. In particular, in AM radio-based PBR, the RD-bin-based signal processing technique was adequately used to transform the range dimension of the CAF into an angular dimension. In this study, we improve the RD-bin-based DOA estimation method for frequency modulation (FM) radio-based PBR. The two main contributions of this paper are as follows. First, we present a criterion for deciding on the number of RD-bins using theoretical analysis. Second, we suggest that other target signals may become interference signals in the presence of multiple targets, which may degrade the DOA estimation accuracy. We also propose a least-squares-based algorithm to solve this problem. From the simulation results, we show that the proposed criterion for deciding on the number of RD-bins is appropriate for FM radio-based PBR and that the proposed least-squares algorithm successfully removes the target interferences.

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Uncued Detection and Initial Orbit Determination From Short Observations With the Murchison Widefield Array

Hennessy

Tingay

Young

et al. 2021

IEEE Aerosp. Electron. Syst. Mag.

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A signal processing scheme for a multichannel passive radar system

Cited by 6 publications

References 8 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

Range-Doppler Domain-Based DOA Estimation Method for FM-Band Passive Bistatic Radar

Uncued Detection and Initial Orbit Determination From Short Observations With the Murchison Widefield Array

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