Suppressing False Alarm in VideoSAR viaGradient-Weighted Edge Information

VideoSAR (Video Synthetic Aperture Radar) technology provides an important mean for real-time and continuous earth observation, whereas the ever-changing scattering characteristics may destroy the accuracy of target motion perception and bring in massive false alarms subsequently. False alarms emerge easily in the edge region for its sharper variations of the scattering characteristics. Utilizing the gradient difference between the target shadow edge and other edge regions in the image, this letter proposes a VideoSAR false alarm reduction method based on gradient-weighted edge information. By considering the reasonable gradient and area of the overlapping edge region between changing region and background, this method could reduce the amount of false alarms ( P f a = 18 . 4 % ) and retain the correct shadow of moving target ( P d = 74 . 8 % ). Experiments on a real footage verify the excellent effect of the proposed method.

Download Full-text

Realizing Target Detection in SAR Images Based on Multiscale Superpixel Fusion

Sensors ◽

10.3390/s21051643 ◽

2021 ◽

Vol 21 (5) ◽

pp. 1643

Author(s):

Ming Liu ◽

Shichao Chen ◽

Fugang Lu ◽

Mengdao Xing ◽

Jingbiao Wei

Keyword(s):

Synthetic Aperture Radar ◽

False Alarm ◽

False Alarm Rate ◽

Target Detection ◽

Synthetic Aperture ◽

False Alarms ◽

Sar Image ◽

Constant False Alarm Rate ◽

Sar Images ◽

Complex Scenes

For target detection in complex scenes of synthetic aperture radar (SAR) images, the false alarms in the land areas are hard to eliminate, especially for the ones near the coastline. Focusing on the problem, an algorithm based on the fusion of multiscale superpixel segmentations is proposed in this paper. Firstly, the SAR images are partitioned by using different scales of superpixel segmentation. For the superpixels in each scale, the land-sea segmentation is achieved by judging their statistical properties. Then, the land-sea segmentation results obtained in each scale are combined with the result of the constant false alarm rate (CFAR) detector to eliminate the false alarms located on the land areas of the SAR image. In the end, to enhance the robustness of the proposed algorithm, the detection results obtained in different scales are fused together to realize the final target detection. Experimental results on real SAR images have verified the effectiveness of the proposed algorithm.

Download Full-text

Accurate detection method of moving target based on sequential SAR images with multiple azimuth squint angles

Journal of Physics Conference Series ◽

10.1088/1742-6596/2083/3/032051 ◽

2021 ◽

Vol 2083 (3) ◽

pp. 032051

Author(s):

Shiqi Yang ◽

Yang Liu ◽

Peili Xi ◽

Chunsheng Li ◽

Wei Yang ◽

...

Keyword(s):

False Alarm ◽

Detection Method ◽

Synthetic Aperture ◽

Moving Target ◽

Constant False Alarm Rate ◽

Moving Targets ◽

Sar Images ◽

Block Level ◽

Detection Block ◽

Motion Characteristics

Abstract In this paper, a novel moving target detection method for sequential Synthetic Aperture Radar (SAR) images with different azimuth-squint angles is proposed. In sequential SAR images, due to the movement of the target, the imaging position of moving targets among different frames differs. The method proposed in this paper uses this kind of motion characteristics to achieve the detection of moving targets in multi-frame SAR images. This algorithm can be divided into two parts: block-level detection and pixel-level detection. Block-level detection is achieved by stacked denoising autoencoders to extract the high-dimensional features of the moving target. Pixel-level detection consists of Local Binary Similarity Patterns (LBSP) coding as well as grayscale background subtraction. Pixel-level detection only needs to consider the pixels of foreground image pieces which contain moving targets. This method can not only increase the detection speed, but also suppress the false alarm problem caused by clutter. Experiments are carried out for verifying the validation of the method and the comparison are made between the proposed method and the traditional Constant False Alarm Rate (CFAR) algorithm.

Download Full-text

Detecting Moving Target on Ground Based on Its Shadow by Using VideoSAR

Remote Sensing ◽

10.3390/rs13163291 ◽

2021 ◽

Vol 13 (16) ◽

pp. 3291

Author(s):

Zhihua He ◽

Zihan Li ◽

Xing Chen ◽

Anxi Yu ◽

Tianzhu Yi ◽

...

Keyword(s):

Synthetic Aperture Radar ◽

Target Detection ◽

State Of The Art ◽

Synthetic Aperture ◽

False Alarms ◽

Moving Target ◽

Moving Target Detection ◽

Frame Difference ◽

The Difference ◽

Distinct Features

Video synthetic aperture radar (VideoSAR) can detect and identify a moving target based on its shadow. A slowly moving target has a shadow with distinct features, but it cannot be detected by state-of-the-art difference-based algorithms because of minor variations between adjacent frames. Furthermore, the detection boxes generated by difference-based algorithms often contain such defects as misalignments and fracture. In light of these problems, this study proposed a robust moving target detection (MTD) algorithm for objects on the ground by fusing the background frame detection results and the difference between frames over multiple intervals. We also discuss defects that occur in conventional MTD algorithms. The difference in background frame was introduced to overcome the shortcomings of difference-based algorithms and acquire the shadow regions of objects. This was fused with the multi-interval frame difference to simultaneously extract the moving target at different velocities while identifying false alarms. The results of experiments on empirically acquired VideoSAR data verified the performance of the proposed algorithm in terms of detecting a moving target on the ground based on its shadow.

Download Full-text

1A2-Q01 Development of False Alarm Reduction Method of Metal Detector with Robotic Arm for Humanitarian Demining(Robotics for Hazardous Fields)

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) ◽

10.1299/jsmermd.2011._1a2-q01_1 ◽

2011 ◽

Vol 2011 (0) ◽

pp. _1A2-Q01_1-_1A2-Q01_4

Author(s):

Tetsuya NARITA ◽

Edwardo F. FUKUSHIMA ◽

Shigeo HIROSE

Keyword(s):

False Alarm ◽

Reduction Method ◽

Robotic Arm ◽

Metal Detector ◽

Humanitarian Demining ◽

Alarm Reduction

Download Full-text

Moving Target Detection with Modified Logarithm Background Subtraction and Its Application to the GF-3 Spotlight Mode

Remote Sensing ◽

10.3390/rs11101190 ◽

2019 ◽

Vol 11 (10) ◽

pp. 1190

Author(s):

Wenjie Shen ◽

Wen Hong ◽

Bing Han ◽

Yanping Wang ◽

Yun Lin

Keyword(s):

False Alarm ◽

Target Detection ◽

Background Subtraction ◽

Image Sequence ◽

False Alarms ◽

Moving Target ◽

Constant False Alarm Rate ◽

Moving Targets ◽

Moving Target Detection ◽

Original Algorithm

Spaceborne spotlight SAR mode has drawn attention due to its high-resolution capability, however, the studies about moving target detection with this mode are less. The paper proposes an image sequence-based method entitled modified logarithm background subtraction to detect ground moving targets with Gaofen-3 Single Look Complex (SLC) spotlight SAR images. The original logarithm background subtraction method is designed by our team for airborne SAR. It uses the subaperture image sequence to generate a background image, then detects moving targets by using image sequence to subtract background. When we apply the original algorithm to the spaceborne spotlight SAR data, a high false alarm problem occurs. To tackle the high false alarm problem due to the target’s low signal-to-noise-ratio (SNR) in spaceborne cases, several improvements are made. First, to preserve most of the moving target signatures, a low threshold CFAR (constant false alarm rate) detector is used to get the coarse detection. Second, because the moving target signatures have higher density than false detections in the coarse detection, a modified DBSCAN (density-based spatial-clustering-of-applications-with-noise) clustering method is then adopted to reduce false alarms. Third, the Kalman tracker is used to exclude the residual false detections, due to the real moving target signature having dynamic behavior. The proposed method is validated by real data, the shown results also prove the feasibility of the proposed method for both Gaofen-3 and other spaceborne systems.

Download Full-text