Moving target tracking in marine aerosol environment with single photon lidar system. (April 2020)

• Record Type: Journal Article
• Authors: Wu, Cheng; Xing, Wenge; Feng, Zhijun; Xia, Linghao
• Is Part Of: Optics and lasers in engineering. Volume 127(2020)
• Publication Date: 2020-04
• Subjects: Single photon lidar -- Marine aerosol -- Moving target tracking -- Two-stage dynamic model -- Strong Kalman filter; Lasers in engineering -- Periodicals; Optical measurements -- Periodicals; Optics -- Periodicals; Lasers en ingénierie -- Périodiques; Mesures optiques -- Périodiques; Optique -- Périodiques; 621.36605
• DOI: 10.1016/j.optlaseng.2019.105967
• Languages: English
• ISSNs: 0143-8166

Abstract

Highlights: Track technique is introduced to deal with the discrete scattering point signal of single photon lidar (SPL). The method is feasible for both moving target and static target detection. While the conventional time-correlated single-photon counting histogram threshold method can only detect static targets. In addition, the proposed method has real-time processing capability and can promote the practical application of SPL. A marine aerosol environment is considered, while most of the researches on SPL are focused on clean environment without the consideration of aerosol-induced clutter. The tracking method has been improved both in dynamic model and filter algorithm. The proposed dynamic model includes a series of complex motions to adapt to the dynamics of the target. The proposed filter has an adaptive covariance matrix. Abstract: The track of moving target by single photon lidar (SPL) is investigated in marine aerosol environment. The aerosol-induced clutter severely limits the detection performance of SPL. Conventional time-correlated single-photon counting histogram threshold method can only detect static targets. We introduced track algorithm to deal with the discrete scattering point signal of SPL. Furthermore, a two-stage (TS) dynamic model with an adaptive strong Kalman filter was proposed in SPL tracking technique. The proposed method, referred to TS-SKF, has a better performance than the current statistical model with Kalman filter (KF) and the TS model with KF in simulated marine aerosol environment. Finally, a series of field experiments were conducted with a self-established SPL system to track the moving cargo ships over the sea at Qingdao (35.9°N, 120.3°E), China. Both the moving and static targets can be effectively detected with the TS-SKF method. The results show that the proposed real-time processing algorithm can provide a new sight to promote the practical application of SPL.