Compressive sensing based passive bistatic radar processing using time-domain complex data

Tabassum, Muhammad Naveed; Hadi, Muhammad Abdul; Alshebeili, Saleh

doi:10.1109/isspit.2015.7394414

Cited by 2 publications

(5 citation statements)

References 14 publications

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“…Comparative Analysis. We compare the proposed method with the time-delay/Doppler combination dictionary-based CS-PR method (named as original method here) presented in [17,18] and Feng et al's method presented in [19]. Table 1 demonstrates the signal model, dictionary size of the original method, Feng et al's method, and the proposed method, respectively.…”

Section: Summary Of Methods Flowmentioning

confidence: 99%

“…CS has been widely used in the field of radar signal processing; it has great potential in improving resolution [15,16]. With the increasing attention in the field of PR, the RD map of targets for PR can be formulated as a sparse recovery problem, and the works related to CS-based PR processing have been published [17][18][19]. In [17,18], a normal CS-based PR processing scheme was proposed to achieve better range and Doppler resolutions.…”

Section: Introductionmentioning

confidence: 99%

“…With the increasing attention in the field of PR, the RD map of targets for PR can be formulated as a sparse recovery problem, and the works related to CS-based PR processing have been published [17][18][19]. In [17,18], a normal CS-based PR processing scheme was proposed to achieve better range and Doppler resolutions. Due to the fact that the dictionary is composed of the template signals with discrete delays and Doppler shifts, this method has high reconstruction accuracy, but it needs a large amount of storage and calculations.…”

Section: Introductionmentioning

confidence: 99%

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Compressed Sensing‐Based Range‐Doppler Processing Method for Passive Radar

Guo

Zhao

Shan

2021

Wireless Communications and Mobile Computing

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Passive radar (PR) systems use the existing transmitters of opportunity in the environment to perform tasks such as detection, tracking, and imaging. The classical cross-correlation based methods to obtain the range-Doppler map have the problems of high sidelobe and limited resolution due to the influence of signal bandwidth. In this paper, we propose a novel range-Doppler processing method based on compressed sensing (CS), which performs sparse reconstruction in range and Doppler dimensions to achieve high resolution and reduces sidelobe without excessive computational burden. Results from numerical simulations and experimental measurements recorded with the Chinese standard digital television terrestrial broadcasting (DTTB) based PR show that the proposed method successfully handles the range-Doppler map formatting problem for PR and outperforms the existing CS-based PR processing methods.

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Section: Summary Of Methods Flowmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Compressed Sensing‐Based Range‐Doppler Processing Method for Passive Radar

Guo

Zhao

Shan

2021

Wireless Communications and Mobile Computing

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show abstract

“…In the PR application,

y ()(, t)

can be written as a linear combination of L basis vectors

y_{I} = y ()(, t) = \sum_{l = 1}^{L} α_{l} φ_{l} (t) + n ()(, t) = {bold-italicψ}_{I} {bold-italicα}_{I} + n ()(, t)

The set

{bold-italicψ}_{I} = (}{, φ_{1}, φ_{2}, \dots φ_{L})

is called dictionary. To construct the columns of

ψ

, it is necessary to consider many delay‐Doppler pairs arising from differential delays associated with targets’ spatial positions as well as finite number of possible velocities [8]. The dictionary in the i th column (also called as atom) (see Fig.…”

Section: Cs Model Of Passive Radarmentioning

confidence: 99%

“…CS‐based radar is able to provide better resolution [6, 7]. Recently, CS is used in monostatic or multistatic radar system to estimate the range and Doppler frequency of targets [8–10].…”

Section: Introductionmentioning

confidence: 99%