Range cell migration correction for dim maneuvering target detection

Tian, Xin; Zhang, Shunsheng; Pang, Linna

doi:10.1109/radar.2014.6875789

Cited by 6 publications

(7 citation statements)

References 11 publications

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“…In this section, we investigate the behavior of the proposed architectures in terms of probability of detection (P d ), computational complexity, and mean value of misclassified pulses (MVMP) defined as the sum of the number of pulses containing target components but classified as noise and the number of noise-only pulses classified as target (this metric is estimated only for the TSAs since OSAs inherit the selection capabilities of BIC). The competitors are the likelihood ratio test assuming perfect knowledge of l, h, and M (clairvoyant detector), the GAMF and the generalized adaptive subspace detector (GASD) [16] both over data from two range cells, and the best detector of [14] defined by (10) and (11) (2S-GIC) and fed by data from the first range bin. Notice that the clairvoyant detector represents an upper bound for the performance.…”

Section: Performance Assessmentmentioning

confidence: 99%

“…To this end, radar systems transmit long bursts of pulses and integrate the corresponding backscattered energy. However, dim maneuvering targets can move through more than one range cell within the integration time interval [10]. As a consequence, it prevents conventional decision schemes from exploiting all the backscattered energy, since they are fed by the range bin under test only and, hence, do not account for the target migration to the contiguous range bin.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, methods to cope with range cell migration (RCM) become of primary importance. A widely used tool for RCM compensation is the Keystone transform which has been applied in several fields as, for instance, radar detection [10] to mitigate target RCM due to radial velocity and acceleration, synthetic aperture radar imaging [11], [12] where the RCM is caused by linear range walk and range curvature. In [13], an alternative method relying on adjacent correlation function and Lv's transform is devised to detect the maneuvering targets with radial jerk motion.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive Detection of Dim Maneuvering Targets in Adjacent Range Cells

Yan

Addabbo

Chen

et al. 2021

IEEE Signal Process. Lett.

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This letter addresses the detection problem of dim maneuvering targets in the presence of range cell migration. Specifically, it is assumed that the moving target can appear in more than one range cell within the transmitted pulse train. Then, the Bayesian information criterion and the generalized likelihood ratio test design procedure are jointly exploited to come up with six adaptive decision schemes capable of estimating the range indices related to the target migration. The computational complexity of the proposed detectors is also studied and suitably reduced. Simulation results show the effectiveness of the newly proposed solutions also for a limited set of training data and in comparison with suitable counterparts.

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Section: Performance Assessmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Adaptive Detection of Dim Maneuvering Targets in Adjacent Range Cells

Yan

Addabbo

Chen

et al. 2021

IEEE Signal Process. Lett.

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“…Therefore, this method applies to only cases in which the SNR is not too low. Tian et al [10] and Dai and Zhang [11] proposed the generalized keystone transform, which can eliminate range migration caused by target motion of the second order and above (acceleration and jerk). Li et al [12] proposed a fast algorithm to process the result of the generalized keystone transform.…”

Section: Introductionmentioning

confidence: 99%

A Signal Processing Algorithm Based on 2D Matched Filtering for SSAR

Yang

Kunhui

et al. 2017

Mathematical Problems in Engineering

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This study discusses a smart radar antenna scanning mode that combines features of both the sector-scan mode used for conventional radar and the line-scan mode used for synthetic aperture radar (SAR) and achieves an application of the synthetic aperture technique in the conventional sector-scan (mechanically scanned) radar, and we refer to this mode as sector-scan synthetic aperture radar (SSAR). The mathematical model is presented based on the principle of SSAR, and a signal processing algorithm is proposed based on the idea of two-dimensional (2D) matched filtering. The influences of the line-scan range and speed on the SSAR system are analyzed, and the solution to the problem that the target velocity is very high is given. The performance of the proposed algorithm is evaluated through computer simulations. The simulation results indicate that the proposed signal processing algorithm of SSAR can gather the signal energy of targets, thereby improving the ability to detect dim targets.

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“…Unfortunately, conventional KT can only correct the first-order RM. Thus [6][7][8] studied second-order KT to correct the second-order RM and Kong et al [9] proposed a coherent integration method via generalized KT and generalized dechirp process (GKTGDP) for maneuvering targets with arbitrary high-order RM. It is worth paying attention to that KT could be invalid without ambiguity correction if Doppler ambiguity happens.…”

Section: Introductionmentioning

confidence: 99%

A Fast Algorithm of Generalized Radon-Fourier Transform for Weak Maneuvering Target Detection

Xia

Zhou

Jin

et al. 2016

International Journal of Antennas and Propagation

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The generalized Radon-Fourier transform (GRFT) has been proposed to detect radar weak maneuvering targets by realizing coherent integration via jointly searching in motion parameter space. Two main drawbacks of GRFT are the heavy computational burden and the blind speed side lobes (BSSL) which will cause serious false alarms. The BSSL learning-based particle swarm optimization (BPSO) has been proposed before to reduce the computational burden of GRFT and solve the BSSL problem simultaneously. However, the BPSO suffers from an apparent loss in detection performance compared with GRFT. In this paper, a fast implementation algorithm of GRFT using the BSSL learning-based modified wind-driven optimization (BMWDO) is proposed. In the BMWDO, the BSSL learning procedure is also used to deal with the BSSL phenomenon. Besides, the MWDO adjusts the coefficients in WDO with Levy distribution and uniform distribution, and it outperforms PSO in a noisy environment. Compared with BPSO, the proposed method can achieve better detection performance with a similar computational cost. Several numerical experiments are also provided to demonstrate the effectiveness of the proposed method.

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Range cell migration correction for dim maneuvering target detection

Cited by 6 publications

References 11 publications

Adaptive Detection of Dim Maneuvering Targets in Adjacent Range Cells

Adaptive Detection of Dim Maneuvering Targets in Adjacent Range Cells

A Signal Processing Algorithm Based on 2D Matched Filtering for SSAR

A Fast Algorithm of Generalized Radon-Fourier Transform for Weak Maneuvering Target Detection

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