Generating Data Matrices on Pulse Radar Phase Detector Output

Perdoch, Jozef; Matousek, Zdenek; Pacek, Miroslav; Gazovova, Stanislava; Ochodnicky, Jan

doi:10.23919/ntsp54843.2022.9920437

Cited by 3 publications

(4 citation statements)

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“…The real part of signal s stored in the data matrix S for SNR = 10 dB is shown as an example in Figure 1 [15].…”

Section: Radar Target Detection On Range‐doppler Mapsmentioning

confidence: 99%

“…The following attributes apply to the data matrix S as shown in Figure 1 [15]: The number of generated signals, which represent reflections from moving radar targets is 5. Ranges of radar targets R = [4.654 5.172 4.308 3.923 2.887] × 10 4 m. Radial speeds of radar targets v r = [–17.68 20.69 20.69 29.78 3.52] m.s −1 . SNR = 10 dB. …”

Section: Radar Target Detection On Range‐doppler Mapsmentioning

confidence: 99%

“…Using such data matrices might find its application in various radar signal processing algorithm designs and their subsequent verification. The above mentioned data matrices might be used in an algorithm for the transformation of the generated radar signal into a form of RD maps [15, 16]. The algorithm for transforming radar data matrix into corresponding RD map is realised by Fourier transform [17, 18].…”

Section: Radar Target Detection On Range‐doppler Mapsmentioning

confidence: 99%

“…The magnitude of the RD map created from data matrix S as shown in Figure 1 is illustrated as an example in Figure 2 [15].…”

Section: Radar Target Detection On Range‐doppler Mapsmentioning

confidence: 99%

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An improved radar clutter suppression by simple neural network

Perďoch,

Gažovová,

Pacek

2023

IET Radar Sonar & Navi

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The presented paper is further focused on the presentation and subsequent assessment of utilising a proposed Neural Network (NN) with simple architecture in the role of a signal preprocessing algorithm for the Constant False Alarm Rate detector and the fixed threshold detector applied on a Range‐Doppler (RD) map with the aim of radar clutter impact reduction and minimisation of processing time. Based on a comparison of all tested algorithm results, it is possible to state that utilising the proposed NN with simple architecture led to reducing the impact of radar clutter when detecting radar targets on RD maps created from provided datasets. Comparing the mean processing time tmean values of all tested algorithms, the authors can state that employing the proposed NN in combination with the fixed threshold detector led to a significant improvement in the computation time needed for processing one RD map while preserving the suppression of radar clutter and detection of the radar targets.

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“…The real part of signal s stored in the data matrix S for SNR = 10 dB is shown as an example in Figure 1 [15].…”

Section: Radar Target Detection On Range‐doppler Mapsmentioning

confidence: 99%