A real-time algorithm for signal detection based on autocorrelation at low SNR

Liu, Shaocheng; Jin, Biao; Yang, Hujun; Su, Tao

doi:10.1109/icosp.2010.5655979

Cited by 5 publications

(3 citation statements)

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“…Step 6: Update the particle position and velocity according to (17) and (18). Output: All the radar source signals are deinterleaved from f (t) and the high-quality radar pulse signal of each radar source.…”

Section: Multi-layer Pso For Pulse Deinterleavingmentioning

confidence: 99%

“…Generally speaking, the acquisition of pulse signal is realized based on signal detection. Reference [18] proposes a shifted-N points-correlation algorithm (SNCA) for non-cooperative target signal detection that can obtain the temporal location of weak signals with unknown parameters. A radar pulse signal can be obtained for subsequent processes based on the detected signal locations.…”

Section: Robust Performance Compared To Conventional Algorithmsmentioning

confidence: 99%

“…Many scholars have devoted themselves to the research of pulse detection and extraction at low SNR. The shift autocorrelation algorithm [18] is a simple and effective low SNR pulse accumulation method for signal detection. It performs well on single-frequency waveforms and linear frequency modulation (LFM) waveforms.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

High-Quality Radar Pulse Signal Acquisition and Deinterleaving under a Low Signal-to-Noise Ratio with Multi-Layer Particle Swarm Optimization

Wei,

Fang,

et al. 2024

Remote Sensing

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Acquiring pulse signals of radar source is an essential component in implementing electronic support measures (ESM). The conventional signal detection or deinterleaving method are mainly applied in relatively simple environments. Currently, radar electronic reconnaissance signal processing capability is severely constrained by poor signal-to-noise ratio (SNR) and the interleaving of signals from various radar sources. This research develops a multi-layer particle swarm optimization (PSO) pulse extraction and deinterleaving technique to improve ESM’s efficacy further. First, coherent accumulation of the received signals is performed using PSO to obtain higher SNR pulse. Second, the signals from this radar source are deinterleaved using the obtained pulse. Ultimately, the aforementioned procedures are combined into a multi-layer PSO architecture to capture radar source signals and deinterleaving them at low SNRs. The suggested algorithm’s efficacy and robustness are confirmed through simulation experiments.

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Section: Multi-layer Pso For Pulse Deinterleavingmentioning

confidence: 99%

Section: Robust Performance Compared To Conventional Algorithmsmentioning

confidence: 99%