Image-Based Target Detection and Radial Velocity Estimation Methods for Multichannel SAR-GMTI

Suwa, Kanenori; Yamamoto, Kazuhiko; Tsuji, Masayoshi; Nakamura, Shohei; Wakayama, Teruhiko; Hara, Teruyuki

doi:10.1109/tgrs.2016.2622712

Cited by 52 publications

(26 citation statements)

References 11 publications

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“…On the one hand, SAR imaging improves the signal-to-noise ratio (SNR) and signal-to-clutter-plus-noise ratio (SCNR) via long-time integration and two-dimensional high resolution, respectively, where the latter isolates and narrows the clutter patch that competes with the moving targets. On the other hand, MC-SAR sensors provide multiple observations of the same scene at different time, which brings in clutter cancellation ability with dual-channel SAR sensors and additional accurate target radial velocity estimation with tri(or more)-channel SAR sensors [ 4 , 8 ]. However, it would be increasingly expensive and technically challenging to design and produce spaceborne SAR sensors with many spatial channels, so that a dual-channel structure is generally applied in state-of-art satellite SAR sensors, such as Radarsat-2, TerraSAR-X and Tandem-X.…”

Section: Introductionmentioning

confidence: 99%

First Spaceborne SAR-GMTI Experimental Results for the Chinese Gaofen-3 Dual-Channel SAR Sensor

Wang

Liao

Zhang

2017

Sensors

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In spaceborne synthetic aperture radar (SAR) sensors, it is a challenging task to detect ground slow-moving targets against strong clutter background with limited spatial channels and restricted pulse repetition frequency (PRF). In this paper, we evaluate the image-based dual-channel SAR-ground moving target indication (SAR-GMTI) workflow for the Gaofen-3 SAR sensor and analyze the impact of strong azimuth ambiguities on GMTI when the displaced phase center antenna (DPCA) condition is not fully satisfied, which has not been demonstrated yet. An effective sliding window design technique based on system parameters analysis is proposed to deal with azimuth ambiguities and reduce false alarm. In the SAR-GMTI experiments, co-registration, clutter suppression, constant false alarm rate (CFAR) detector, vector velocity estimation and moving target relocation are analyzed and discussed thoroughly. With the real measured data of the Gaofen-3 dual-channel SAR sensor, the GMTI capability of this sensor is demonstrated and the effectiveness of the proposed method is verified.

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Section: Introductionmentioning

confidence: 99%

First Spaceborne SAR-GMTI Experimental Results for the Chinese Gaofen-3 Dual-Channel SAR Sensor

Wang

Liao

Zhang

2017

Sensors

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“…If the pixels in the cluster space K i − 1 , K i , K i + 1 belong to the same type of target, then the value of Δu i11 , Δu i , Δu i + 1 will be very small after clustering, so that l ≈ 1 can be obtained from the analogy of Eqs. (5) and (6). The meaning is that the linear relationship between the three types of cluster centers belonging to the same type of target before and after clustering should not be destroyed, and the relative change is small.…”

Section: Fuzzy Clustering Segmentationmentioning

confidence: 99%

“…First, the Hough detection algorithm was used to detect the area that may contain the ball, and then the neural network classifier was used to find the area containing the ball. In order to further increase the speed, this method introduces background subtraction method and ball tracking technology [6].…”

Section: Introductionmentioning

confidence: 99%

Fitness training driven by image target detection technology

Wang¹,

Li²,

Sun³

et al. 2018

J Image Video Proc.

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The fitness training system needs to capture the training staff dynamics in real time, but it is difficult to capture the training staff dynamics during the actual training process. Based on this, this study uses the physical characteristics of fitness trainers as indicators for image target detection. According to the human body will dissipate more heat during the fitness process, this study uses infrared capture as the basis of image capture detection technology, uses FCM clustering algorithm as the fuzzy image background segmentation algorithm, and uses k-means clustering analysis to study the gray histogram and propose a composite classification feature tracking method for trainer image tracking. Combined with the experimental research, the research shows that the research method utilizes the advantages of the composite classification feature to improve the detection rate of the human target. Therefore, it is a real-time and very effective infrared image human detection algorithm.

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“…Synthetic aperture radar (SAR) is an active microwave imaging sensor that can work independently of time and weather [1]. In recent years, ground moving target indication (GMTI), as one of the most important applications of SAR, has attracted great attention in civilian fields [2,3,4]. Currently, SAR-GMTI research is mainly focused on radar sensors mounted on platforms with a uniform linear trajectory.…”

Section: Introductionmentioning

confidence: 99%

Ground Moving Target 2-D Velocity Estimation and Refocusing for Multichannel Maneuvering SAR with Fixed Acceleration

Tang

Tian

2019

Sensors

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It is difficult for multichannel maneuvering synthetic aperture radar (SAR) to achieve ground moving target 2D velocity estimation and refocusing. In this paper, a novel method based on back projection (BP) and velocity SAR (VSAR) is proposed to cope with the issues. First, the static scene is reconstructed by BP to solve the imaging problem of multichannel maneuvering SAR. Then, the static clutter is suppressed, and the range velocity is estimated via VSAR processing. As for azimuth velocity estimation and refocusing, a velocity search method based on velocity-aided BP (VA-BP) and VSAR is proposed to accomplish them. First, each azimuth velocity in the search and the estimated range velocity are used to image the moving target in a small-sized subimage space by VA-BP, i.e., matching the range history and the Doppler phase of the moving target in the image processing. Then, multiple sets of multichannel SAR subimages corresponding to different azimuth velocities are generated, and the clutter of each set of multichannel SAR subimages is also suppressed by VSAR processing. After that, the azimuth velocity is estimated by searching the clutter-suppressed subimage of the first spatial receiving channel in each set of multichannel SAR subimages with the best refocusing quality measured by the minimum entropy. Simulation results show the proposed method can reach high accuracy in moving target 2D velocity estimation and refocusing with the absolute error of 2D velocity estimation smaller than 0.1 m/s.

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Image-Based Target Detection and Radial Velocity Estimation Methods for Multichannel SAR-GMTI

Cited by 52 publications

References 11 publications

First Spaceborne SAR-GMTI Experimental Results for the Chinese Gaofen-3 Dual-Channel SAR Sensor

First Spaceborne SAR-GMTI Experimental Results for the Chinese Gaofen-3 Dual-Channel SAR Sensor

Fitness training driven by image target detection technology

Ground Moving Target 2-D Velocity Estimation and Refocusing for Multichannel Maneuvering SAR with Fixed Acceleration

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