Results 21 to 30 of about 4,661,211 (242)
Leida xuebao, 2019 Under the clutter background condition, the existing particle filter pre-detection tracking algorithm based on Probability Hypothesis Density (PHD) filtering is not accurate enough to estimate the number of targets in dense multi-objectives.
PEI Jiazheng +4 more
doaj +1 more source
Refined PHD Filter for Multi-Target Tracking under Low Detection Probability
Sensors, 2019 Radar target detection probability will decrease as the target echo signal-to-noise ratio (SNR) decreases, which has an adverse influence on the result of multi-target tracking.
Sen Wang, Qinglong Bao, Zengping Chen
doaj +1 more source
Unscented Auxiliary Particle Filter Implementation of the Cardinalized Probability Hypothesis Density Filters [PDF]
AUT Journal of Electrical Engineering, 2017 The probability hypothesis density (PHD) filter suffers from lack of precise estimation of the expected number of targets. The Cardinalized PHD (CPHD) recursion, as a generalization of the PHD recursion, remedies this flaw and simultaneously propagates ...
M. R. Danaee, F. Behnia
doaj +1 more source
Regional variance for multi-object filtering [PDF]
, 2014 Recent progress in multi-object filtering has led to algorithms that compute the first-order moment of multi-object distributions based on sensor measurements.
Delande, Emmanuel D +5 more
core +1 more source
Extended Target Tracking with a Cardinalized Probability Hypothesis Density Filter
, 2011 This paper presents a cardinalized probability hypothesis density (CPHD) filter for extended targets that can result in multiple measurements at each scan.
Orguner, Umut +2 more
core +4 more sources
Leida xuebao, 2017 Due to the Doppler Blind Zone (DBZ), the target tracking of Doppler radar becomes more and more complicated. In this paper, a multi-target tracking algorithm based on Gaussian Mixture Probability Hypothesis Density (GM-PHD) for DBZ is proposed.
Wei Qiang, Liu Zhong
doaj +1 more source
Multitarget Tracking Using One Time Step Lagged Delta-Generalized Labeled Multi-Bernoulli Smoothing
IEEE Access, 2020 Aiming at improving the tracking performance of the delta-generalized labeled multi-Bernoulli (δ-GLMB) filter, we present a one time step lagged δ-GLMB smoother in this work, which also inherently outputs targets trajectories and differs ...
Guolong Liang +3 more
doaj +1 more source
Multiple Object Tracking Based on Background Subtraction Detection and Improved GM-PHD Filter [PDF]
Jisuanji gongcheng, 2017 Target label confusion and loss are usually caused by occlusion and detection missing in multiple object tracking process,which leads to failing tracking.Aiming at this problem,an improved tracking method based on Gaussian Mixture Probability Hypothesis ...
CHEN Xiangqian,MA Shaohui,XU Wenbo
doaj +1 more source
Trajectory probability hypothesis density filter [PDF]
, 2018 This paper presents the probability hypothesis density (PHD) filter for sets of trajectories: the trajectory probability density (TPHD) filter. The TPHD filter is capable of estimating trajectories in a principled way without requiring to evaluate all ...
García-Fernández, ÁF, Svensson, L
core +1 more source
MULTI-TARGET DETECTION FROM FULL-WAVEFORM AIRBORNE LASER SCANNER USING PHD FILTER [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 We propose a new technique to detect multiple targets from full-waveform airborne laser scanner. We introduce probability hypothesis density (PHD) filter, a type of Bayesian filtering, by which we can estimate the number of targets and their positions ...
T. Fuse, D. Hiramatsu, W. Nakanishi
doaj +1 more source