Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/194482
Title: Range–Doppler-based centralised framework for human target tracking in multistatic radar
Authors: Jun Zhang;Tian Jin;Yuan He;Lei Qiu;Zhimin Zhou
Year: 2017
Publisher: IET
Abstract: Human target detection and tracking have great potential in surveillance, rescue and security applications. Traditional human detection and tracking are performed on the range profile. If targets are close or overlapped in range, it is difficult to distinguish these targets. As velocity provides another aspect to distinguish targets, a novel framework is proposed for human tracking using both range and velocity information. The tracking framework consists of six steps, including clutter reduction, range-Doppler (RD) calculation, target detection, measurement estimation, target localisation and target tracking. Primary attention is devoted to the middle four steps. The calculation process of the RD image is described in detail. The ordered statistics constant false alarm rate detector is extended to a two-dimensional scenario for the RD target detection. An efficient approach is given for automatic measurement estimation. A minimum root-mean-square error pruning algorithm is proposed for multi-target localisation. As the algorithm combines both range and velocity information for measurement association, it clearly shows a lower wrong association probability than the method using range information only. The effectiveness of the proposed tracking framework is evaluated by the experimental data in the foliage-penetration environment.
URI: http://localhost/handle/Hannan/194482
volume: 11
issue: 1
More Information: 193,
203
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7843575.pdf4.96 MBAdobe PDF
Title: Range–Doppler-based centralised framework for human target tracking in multistatic radar
Authors: Jun Zhang;Tian Jin;Yuan He;Lei Qiu;Zhimin Zhou
Year: 2017
Publisher: IET
Abstract: Human target detection and tracking have great potential in surveillance, rescue and security applications. Traditional human detection and tracking are performed on the range profile. If targets are close or overlapped in range, it is difficult to distinguish these targets. As velocity provides another aspect to distinguish targets, a novel framework is proposed for human tracking using both range and velocity information. The tracking framework consists of six steps, including clutter reduction, range-Doppler (RD) calculation, target detection, measurement estimation, target localisation and target tracking. Primary attention is devoted to the middle four steps. The calculation process of the RD image is described in detail. The ordered statistics constant false alarm rate detector is extended to a two-dimensional scenario for the RD target detection. An efficient approach is given for automatic measurement estimation. A minimum root-mean-square error pruning algorithm is proposed for multi-target localisation. As the algorithm combines both range and velocity information for measurement association, it clearly shows a lower wrong association probability than the method using range information only. The effectiveness of the proposed tracking framework is evaluated by the experimental data in the foliage-penetration environment.
URI: http://localhost/handle/Hannan/194482
volume: 11
issue: 1
More Information: 193,
203
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7843575.pdf4.96 MBAdobe PDF
Title: Range–Doppler-based centralised framework for human target tracking in multistatic radar
Authors: Jun Zhang;Tian Jin;Yuan He;Lei Qiu;Zhimin Zhou
Year: 2017
Publisher: IET
Abstract: Human target detection and tracking have great potential in surveillance, rescue and security applications. Traditional human detection and tracking are performed on the range profile. If targets are close or overlapped in range, it is difficult to distinguish these targets. As velocity provides another aspect to distinguish targets, a novel framework is proposed for human tracking using both range and velocity information. The tracking framework consists of six steps, including clutter reduction, range-Doppler (RD) calculation, target detection, measurement estimation, target localisation and target tracking. Primary attention is devoted to the middle four steps. The calculation process of the RD image is described in detail. The ordered statistics constant false alarm rate detector is extended to a two-dimensional scenario for the RD target detection. An efficient approach is given for automatic measurement estimation. A minimum root-mean-square error pruning algorithm is proposed for multi-target localisation. As the algorithm combines both range and velocity information for measurement association, it clearly shows a lower wrong association probability than the method using range information only. The effectiveness of the proposed tracking framework is evaluated by the experimental data in the foliage-penetration environment.
URI: http://localhost/handle/Hannan/194482
volume: 11
issue: 1
More Information: 193,
203
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7843575.pdf4.96 MBAdobe PDF