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Author

Jian Guan

Bio: Jian Guan is an academic researcher. The author has contributed to research in topics: Clutter & Radar. The author has an hindex of 14, co-authored 70 publications receiving 1080 citations.


Papers
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Journal ArticleDOI
TL;DR: The results demonstrate that for integration gain and detection ability, the proposed method is superior to MTD, FRFT, and Radon-Fourier transform under low signal-to-clutter/noise ratio (SCR/SNR) environments.
Abstract: Long-time coherent integration technique is one of the most important methods for the improvement of radar detection ability of a weak maneuvering target, whereas the integration performance may be greatly influenced by the across range unit (ARU) and Doppler frequency migration (DFM) effects. In this paper, a novel representation known as Radon-fractional Fourier transform (RFRFT) is proposed and investigated to solve the above problems simultaneously. It can not only eliminate the effect of DFM by selecting a proper rotation angle but also achieve long-time coherent integration without ARU effect. The RFRFT can be regarded as a special Doppler filter bank composed of filters with different rotation angles, which indicates a generalization of the traditional moving target detection (MTD) and FRFT methods. Some useful properties and the likelihood ratio test detector of RFRFT are derived for maneuvering target detection. Finally, numerical experiments of aerial target and marine target detection are carried out using simulated and real radar datasets. The results demonstrate that for integration gain and detection ability, the proposed method is superior to MTD, FRFT, and Radon-Fourier transform under low signal-to-clutter/noise ratio (SCR/SNR) environments. Moreover, the trajectory of target can be easily obtained via RFRFT as well.

304 citations

Journal ArticleDOI
TL;DR: The results demonstrate that the proposed method not only achieves high detection probability in a low-SCR environment but also outperforms the short-time Fourier transform-based method.
Abstract: In order to effectively detect moving targets in heavy sea clutter, the micro-Doppler (m-D) effect is studied and an effective algorithm based on short-time fractional Fourier transform (STFRFT) is proposed for target detection and m-D signal extraction. Firstly, the mathematical model of target with micromotion at sea, including translation and rotation movement, is established, which can be approximated as the sum of linear-frequency-modulated signals within a short time. Then, due to the high-power, time-varying, and target-like properties of sea spikes, which may result in poor detection performance, sea spikes are identified and eliminated before target detection to improve signal-to-clutter ratio (SCR). By taking the absolute amplitude of signals in the best STFRFT domain (STFRFD) as the test statistic, and comparing it with the threshold determined by a constant false alarm rate detector, micromotion target can be declared or not. STFRFT with Gaussian window is employed to provide time-frequency distribution of m-D signals, and the instantaneous frequency of each component can be extracted and estimated precisely by STFRFD filtering. In the end, datasets from the intelligent pixel processing radar with HH and VV polarizations are used to verify the validity of this proposed algorithm. Two shore-based experiments are also conducted using an X-band sea search radar and an S-band sea surveillance radar, respectively. The results demonstrate that the proposed method not only achieves high detection probability in a low-SCR environment but also outperforms the short-time Fourier transform-based method.

147 citations

Journal ArticleDOI
TL;DR: In this paper, a novel adaptive algorithm in fractional Fourier transform (FRFT) domain is proposed, which combines statistic-based and FRFT-based detection method, which provides less error and faster convergence.
Abstract: Attention has been focused on the moving target detection in heavy sea clutter. On the basis of detection model of moving target with fluctuant amplitudes, a novel adaptive algorithm in fractional Fourier transform (FRFT) domain is proposed, which combines statistic-based and FRFT-based detection method. FRFT has good energy concentration property on linear frequency modulation (LFM) signal with the optimal transform angle, which is determined by calculating spectral kurtosis (SK) in FRFT domain. Grading iterative search method is used for good accuracy of parameter estimation and fast calculation speed. A novel adaptive line enhancer (ALE) in FRFT domain is proposed to suppress sea clutter and improve signal-to-clutter ratio (SCR), which provides less error and faster convergence. Leakage factor is introduced into the update equation of weight vector to reduce `memory effect` and step size is normalised by the power of input signal with better convergence characteristic. In the end, both X-band and S-band real sea clutter is used for verification and the results present that the proposed algorithm has good convergence property and small mean square error (MSE). Weak moving target in low SCR environment (SCR = -6 dB) can be well detected and estimated, which indicates the effectiveness of the algorithm.

94 citations

Journal ArticleDOI
TL;DR: It is drawn that it is impossible to obtain a beampattern merely focusing on some specific spatial positions and lasting for some specific time.
Abstract: The frequency diverse array (FDA) radar has drawn great attention due to the periodicity of the beampattern in range, angle, and time. In this letter, we restudy the recent work that designed a time-invariant beampattern of the FDA radar, which can focus the transmit energy in a desired position. We reanalyze the derivation of the FDA beampattern synthesis and point out the neglected constraint condition, which leads the research of the FDA beampattern synthesis to an impractical direction. By comparing the replication of one of the prior works with our result, we draw a conclusion that it is impossible to obtain a beampattern merely focusing on some specific spatial positions and lasting for some specific time.

79 citations

Journal ArticleDOI
TL;DR: Experiments with simulated and real radar data sets indicate that the proposed RLCAF can achieve higher integration gain and detection probability of a marine target in a low signal-to-clutter ratio environment.
Abstract: Robust and effective detection of a marine target is a challenging task due to the complex sea environment and target's motion. A long-time coherent integration technique is one of the most useful methods for the improvement of radar detection ability, whereas it would easily run into the across range unit (ARU) and Doppler frequency migration (DFM) effects resulting distributed energy in the time and frequency domain. In this paper, the micro-Doppler (m-D) signature of a marine target is employed for detection and modeled as a quadratic frequency-modulated signal. Furthermore, a novel long-time coherent integration method, i.e., Radon-linear canonical ambiguity function (RLCAF), is proposed to detect and estimate the m-D signal without the ARU and DFM effects. The observation values of a micromotion target are first extracted by searching along the moving trajectory. Then these values are carried out with the long-time instantaneous autocorrelation function for reduction of the signal order, and well matched and accumulated in the RLCAF domain using extra three degrees of freedom. It can be verified that the proposed RLCAF can be regarded as a generalization of the popular ambiguity function, fractional Fourier transform, fractional ambiguity function, and Radon-linear canonical transform. Experiments with simulated and real radar data sets indicate that the RLCAF can achieve higher integration gain and detection probability of a marine target in a low signal-to-clutter ratio environment.

76 citations


Cited by
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Journal ArticleDOI
TL;DR: The results demonstrate that for integration gain and detection ability, the proposed method is superior to MTD, FRFT, and Radon-Fourier transform under low signal-to-clutter/noise ratio (SCR/SNR) environments.
Abstract: Long-time coherent integration technique is one of the most important methods for the improvement of radar detection ability of a weak maneuvering target, whereas the integration performance may be greatly influenced by the across range unit (ARU) and Doppler frequency migration (DFM) effects. In this paper, a novel representation known as Radon-fractional Fourier transform (RFRFT) is proposed and investigated to solve the above problems simultaneously. It can not only eliminate the effect of DFM by selecting a proper rotation angle but also achieve long-time coherent integration without ARU effect. The RFRFT can be regarded as a special Doppler filter bank composed of filters with different rotation angles, which indicates a generalization of the traditional moving target detection (MTD) and FRFT methods. Some useful properties and the likelihood ratio test detector of RFRFT are derived for maneuvering target detection. Finally, numerical experiments of aerial target and marine target detection are carried out using simulated and real radar datasets. The results demonstrate that for integration gain and detection ability, the proposed method is superior to MTD, FRFT, and Radon-Fourier transform under low signal-to-clutter/noise ratio (SCR/SNR) environments. Moreover, the trajectory of target can be easily obtained via RFRFT as well.

304 citations

Journal ArticleDOI
He Deng1, Xianping Sun1, Maili Liu1, Chaohui Ye1, Xin Zhou1 
TL;DR: Experimental results demonstrate that the proposed WLDM-based algorithm not only works more robustly for different cloudy-sky backgrounds, target movements, and signal-to-clutter ratio (SCR) values but also has a better performance with regard to the detection accuracy, in comparison to traditional baseline methods.
Abstract: Against an intricate infrared cloudy-sky background, jamming objects such as the edges of clouds in the scene have a similar thermal intensity measure with respect to the background as small targets. This may cause high false alarm rates and low probabilities of detection according to conventional small target detection methods. In this paper, we propose a weighted local difference measure (WLDM)-based scheme for the detection of small targets against various complex cloudy-sky backgrounds. Initially, a WLDM map is achieved to simultaneously enhance targets and suppress background clutters and noise. In this way, the true targets can be easily separated from jamming objects. After that, a simple adaptive threshold is used to segment the targets. More than 460 infrared small target images against diverse intricate cloudy-sky backgrounds were utilized to validate the detection capability of the WLDM-based method. Experimental results demonstrate that the proposed algorithm not only works more robustly for different cloudy-sky backgrounds, target movements, and signal-to-clutter ratio (SCR) values but also has a better performance with regard to the detection accuracy, in comparison to traditional baseline methods. In particular, the proposed method is able to significantly improve SCR values of the images.

221 citations

Journal ArticleDOI
TL;DR: This letter considers the coherent integration problem for a maneuvering target, involving range migration (RM) and Doppler frequency migration (DFM) within one coherent pulse interval, and proposes a new coherent integration method, known as Radon-Lv's distribution (RLVD), which can not only eliminate the RM effect via jointly searching in the target's motion parameters space, but also remove the DFM.
Abstract: This letter considers the coherent integration problem for a maneuvering target, involving range migration (RM) and Doppler frequency migration (DFM) within one coherent pulse interval. A new coherent integration method, known as Radon-Lv’s distribution (RLVD), is proposed. It can not only eliminate the RM effect via jointly searching in the target’s motion parameters space, but also remove the DFM and achieve the coherent integration via Lv’s distribution (LVD). Finally, several simulations are provided to demonstrate the effectiveness. The results show that for detection ability, the proposed method is superior to the moving target detection (MTD), Radon-Fourier transform (RFT), and Radon-fractional Fourier transform (RFRFT) under low signal-to-noise-ratio (SNR) environment.

157 citations

Journal ArticleDOI
TL;DR: The results demonstrate that the proposed method not only achieves high detection probability in a low-SCR environment but also outperforms the short-time Fourier transform-based method.
Abstract: In order to effectively detect moving targets in heavy sea clutter, the micro-Doppler (m-D) effect is studied and an effective algorithm based on short-time fractional Fourier transform (STFRFT) is proposed for target detection and m-D signal extraction. Firstly, the mathematical model of target with micromotion at sea, including translation and rotation movement, is established, which can be approximated as the sum of linear-frequency-modulated signals within a short time. Then, due to the high-power, time-varying, and target-like properties of sea spikes, which may result in poor detection performance, sea spikes are identified and eliminated before target detection to improve signal-to-clutter ratio (SCR). By taking the absolute amplitude of signals in the best STFRFT domain (STFRFD) as the test statistic, and comparing it with the threshold determined by a constant false alarm rate detector, micromotion target can be declared or not. STFRFT with Gaussian window is employed to provide time-frequency distribution of m-D signals, and the instantaneous frequency of each component can be extracted and estimated precisely by STFRFD filtering. In the end, datasets from the intelligent pixel processing radar with HH and VV polarizations are used to verify the validity of this proposed algorithm. Two shore-based experiments are also conducted using an X-band sea search radar and an S-band sea surveillance radar, respectively. The results demonstrate that the proposed method not only achieves high detection probability in a low-SCR environment but also outperforms the short-time Fourier transform-based method.

147 citations

Journal ArticleDOI
TL;DR: Compared with the generalized Radon Fourier transform (GRFT), the proposed method can acquire a close integration performance but with lower computational complexity since the parameter searching dimension is reduced.
Abstract: In the airborne or spaceborne radar applications, prolonging the coherent integration time is one of the effective methods to improve the radar detection ability of a weak maneuvering target, whereas the coherent integration performance may degrade due to the complex range migration (RM) and Doppler frequency migration (DFM) effects. In this paper, detection and motion parameter estimation for a weak maneuvering target with the third-order RM and DFM are considered. Firstly, Keystone transform is applied to compensate the linear range walk. Then, the matched filtering processing is performed in the range-frequency and azimuth-time domain to eliminate the residual coupling effects between range and azimuth. Finally, a well-focused image of a moving target is obtained, and three motion parameters, i.e., velocity, acceleration, and acceleration rate, are effectively estimated. In addition, as for a fast-moving target with Doppler ambiguity, two cases, i.e., target azimuth spectrum within a pulse repetition frequency (PRF) and spanning over neighboring PRF bands, are analyzed. Compared with the generalized Radon Fourier transform (GRFT), the proposed method can acquire a close integration performance but with lower computational complexity since the parameter searching dimension is reduced. Simulated processing results are provided to validate the effectiveness of the proposed method.

144 citations