Coherent Integration for Maneuvering Target Detection Based on Radon-Lv’s Distribution

Li, Xiaolong; Cui, Guolong; Yi, Wei; Kong, Lingjiang

doi:10.1109/lsp.2015.2390777

Cited by 177 publications

(103 citation statements)

References 21 publications

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“…In (10), it is shown that the cubic term, the quadratic term and the first-order term of slow time t are all coupled with the range frequency f , which would result in respectively TRM, SRM and FRM within the coherent integration time. Additionally, the quadratic term and cubic term of t will bring about Doppler frequency migration (DFM) [9], [26] which may make the signal energy defocused.…”

Section: Substituting (6) Into (5) Yieldsmentioning

confidence: 99%

“…The performance of target detection affects the imaging quality, target tracking and identification significantly [5]- [7]. It is known that the coherent integration can increase the signal-to-noise-ratio (SNR) and thus improve the radar detection ability, via compensating the target's phase fluctuation among multiple radar pulse samplings [8]- [10]. Unfortunately, the complex motions of maneuvering targets, e.g., high velocity, acceleration and jerk, involves the first-order range migration (FRM), second-order range migration (SRM) and third-order range migration (TRM) within the coherent integration time, which result in serious performance loss for the coherent integration processing.…”

Section: Introductionmentioning

confidence: 99%

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Coherent Integration Algorithm for a Maneuvering Target With High-Order Range Migration

Kong

Cui

et al. 2015

IEEE Trans. Signal Process.

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128

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This paper considers the coherent integration problem for a maneuvering target with complex motions, where the velocity, acceleration and jerk result in respectively the first-order range migration (FRM), second-order range migration (SRM) and third-order range migration (TRM) within the coherent pulse interval. A new coherent integration algorithm based on generalized keystone transform (KT) and secondorder dechirp process is proposed, which employs the third-order KT, six-order KT, second-order KT and fold factor searching to correct the TRM, SRM and FRM, respectively. The range migration change during each step and computational complexity are also theoretically analyzed. Compared with the generalized Radon Fourier transform (GRFT) algorithm, the presented method can avoid the blind speed sidelobe (BSSL) and acquire close integration performance but with much lower computational cost. Simulations are provided to demonstrate the effectiveness. Finally, a generalized method, named generalized KT and generalized dechirp process (GKTGDP), is also introduced for the maneuvering target with arbitrary high-order range migration.Maneuvering target, coherent integration, third-order range migration, generalized keystone transform, range migration correction.1053-587X (c) , IEEE Transactions on Signal Processing 3 for coherent integration due to the TRM. The generalized Radon Fourier transform (GRFT) was then presented to remove the TRM and conduct the coherent integration processing [15], [21]. Although GRFT can obtain coherent accumulation via jointly searching in target's motion parameter space, it has two limitations. Firstly, because of discrete pulse sampling, finite range resolution and limited integration time, the blind speed sidelobe (BSSL) may inevitably appear in the GRFT output, which leads to serious false alarm and detection performance deterioration [22]. A BSSL suppression method, based on the minimum operator of two weighted GRFT outputs, was studied in [22]. Nevertheless, it requires to bisect the coherent integration period, thus the integration performance would be decreased by about 3 dB.Secondly, the GRFT method is often computationally prohibitive, since it involves the solution of a fourdimensional searching. An improved particle swarm optimization (PSO) was then introduced to reduce the computational burden of GRFT [23]. However, the PSO may sensitive to the initial parameters set and get trapped in the local optimization for the scenario of multiple targets. This paper considers the coherent integration problem for a maneuvering target with jerk motion, involving TRM, SRM and FRM within the coherent pulse interval. A new coherent integration method based on generalized KT and second-order dechirp process (SDP) is proposed, where the third-order KT, six-order KT, second-order KT and fold factor searching are respectively employed to remove the TRM, SRM and FRM. After that, cross range Fourier transform (FT) is carried out to achieve the coherent accumulation of target energy. We also theoretica...

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Section: Substituting (6) Into (5) Yieldsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Coherent Integration Algorithm for a Maneuvering Target With High-Order Range Migration

Kong

Cui

et al. 2015

IEEE Trans. Signal Process.

Self Cite

128

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show abstract

“…To jointly correct and compensate for the ARC and DS, Xu, et al [27] introduced a method known as generalized Radon Fourier transform (GRFT), which is the extension of the original RFT algorithm. In addition, Li, et al [28] proposed an algorithm named Radon Lv's distribution (RLVD) to accumulate and detect weak target signals, while Chen, et al [29] proposed the Radon Fractional Fourier transform (RFRFT) for a maneuvering target detection. To some extent, these two algorithms [28,29] also can be regarded as the expansion and extension of the RFT, since both RLVD and RFRFT eliminate the ARC and DS simultaneously by searching in the range-velocity-acceleration domain.…”

Section: Introductionmentioning

confidence: 99%

WRFRFT-based coherent detection and parameter estimation of radar moving target with unknown entry/departure time

Sun

Zhang

et al. 2020

Signal Processing

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A moving target may enter a radar coverage area unannounced and leave after an unspecified period, which implies that the target's entry time and departure time are unknown. In the absence of these time information, target detection and parameter estimation (DAPE) will be severely impacted. In this paper, we consider the coherent detection and parameters estimation problem for a radar moving target with unknown entry time and departure time (that is, the time when the target appears-in/leaves the radar detection field is unknown), involving across range cell (ARC) and Doppler spread (DS) effects within the observation period. A new algorithm, known as window Radon Fractional Fourier transform (WRFRFT) is proposed to detect and estimate the target's time parameters (i.e., entry time and departure time) and motion parameters (i.e., range, velocity and acceleration). The observation values of a maneuvering target are first intercepted and extracted by the window function and searching along the motion trajectory. Then these values are fractional Fourier transformed and well accumulated in the WR-FRFT domain, where the DAPE of target could be accomplished thereafter. Experiments with simulated and real radar data sets prove its effectiveness.

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“…As we know, the source localization accuracy depends much on the TDOA and FDOA estimation accuracy. Hence, to improve the performance of radar detection and parameter estimation, some studies aim at the long-time coherent integration [15,16]. Nevertheless, extending the observation time would improve FDOA estimation accuracy, which has contributed to source localization [17], but it will cause serious relative Doppler companding problem [17,18].…”

Section: Introductionmentioning

confidence: 99%

An algebraic method for moving source localization using TDOA, FDOA, and differential Doppler rate measurements with receiver location errors

Liu

Zhao

et al. 2019

EURASIP J. Adv. Signal Process.

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To weaken the effect of receiver location error on localization accuracy and make the localization model closer to the practical scenario, this paper considers the receiver location errors, usually neglected in prior studies into the measurement model, and proposes an algebraic method for locating a moving source using time difference of arrival (TDOA), frequency difference of arrival (FDOA), and differential Doppler rate measurements. The proposed method is based on the pseudo-linear set of equations and two-step weighted least square estimator. Only noise values of receiver locations and three types of positioning measurements are available for processing. In addition, a new Cramér-Rao lower bound (CRLB) combining TDOA, FDOA, and differential Doppler rate in the presence of receiver location errors is also derived in this paper. Theoretical analysis and simulation results both indicate that the proposed method can attain CRLB at a moderate noise level, avoid the rank deficiency problem efficiently, and achieve a significant improvement over the existing methods.

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Coherent Integration for Maneuvering Target Detection Based on Radon-Lv’s Distribution

Cited by 177 publications

References 21 publications

Coherent Integration Algorithm for a Maneuvering Target With High-Order Range Migration

Coherent Integration Algorithm for a Maneuvering Target With High-Order Range Migration

WRFRFT-based coherent detection and parameter estimation of radar moving target with unknown entry/departure time

An algebraic method for moving source localization using TDOA, FDOA, and differential Doppler rate measurements with receiver location errors

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