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Tracking a Ground Target Utilizing Doppler-Only Measurements of a Single Passive Sonar Sensor Assisted by Straight road constraints

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IEEE ACCESS 2022年 10卷 74198-74206页

作者： Kim, Jonghoek Sungkyunkwan Univ Dept Elect & Elect Engn Suwon 16419 South Korea

This paper handles tracking a ground target using a single passive sonar sensor measuring doppler shift of the target. We consider a scenario where the frequency of the emitting tone is not known in advance. We further consider a ground target which is constrained to move along a known straight road with a known course. It is assumed that the single sonar sensor is located close to the road, whose shape is known in advance. This article introduces tracking the ground target assisted by road constraints. We address a non-recursive estimation algorithm using a batch filter initialized with samples that are distributed considering the road constraints. As far as we know, our paper is unique in using a single sonar sensor for target localization with doppler-only measurements with unknown emitting frequency. Moreover, our article is unique in target tracking based on doppler-only measurements of a single sonar sensor, assisted by road constraints. The effectiveness of the proposed tracking filter is verified under MATLAB simulations.

关键词： Target tracking roads Sonar measurements Sonar Radar tracking Doppler shift Doppler measurement Doppler-only measurements road constraints course constraints constrained target tracking passive sonar sensor

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Bernoulli Filter with Linear Equality constraints 18

Bernoulli Filter with Linear Equality Constraints

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18th International Conference on Information Fusion (Fusion)

作者： Yang, Feng Zhang, Wanying Northwestern Polytech Univ Sch Automat Minist Educ Key Lab Informat Fus Technol Xian Shaanxi Peoples R China

ISBN: (纸本)9780982443866

Bernoulli filters are used to estimate the states of dynamic systems recently. However, in the application of tracking ground moving targets in clutter, some valuable information tend to be ignored, such as the road constraints. The road constraints, as prior information about the state, should be incorporated into the dynamic modeling process of the filtering algorithm. In this paper, a method of incorporating state linear equality constraints (LEC) into the Bernoulli filter called the LEC Bernoulli filter (LECBF) is presented for tracking ground moving target. In this case, the Bernoulli filter is improved by exploiting road constraints, and can achieve a better filtering performance than the original unconstrained Bernoulli filter. Finally, an illustrative example is provided to show the effectiveness and efficiency of the LECBF.

关键词： Bernoulli filters ground target tracking road constraints dynamics modeling linear equality constraint

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road-Constrained Geometric Pose Estimation for Ground Vehicles

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2020年第2期17卷 748-760页

作者： Jiang, Rui Zhou, Hui Wang, Han Ge, Shuzhi Sam Natl Univ Singapore Dept Elect & Comp Engn Singapore 117583 Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Qingdao Univ Inst Future IFF Qingdao 266071 Peoples R China

Pose estimation with state or measurement constraints has been frequent in autonomous vehicle navigation. Aiming at incorporating constraints inherently, this article proposes a dynamic potential field (DPF)-based formulation to represent states, measurements, and constraints on connected Riemannian manifolds. The state equation and the output equation are derived in the DPF forms, which imply the probabilistic inference with states and measurements. constraints are incorporated by projecting points toward a constraint subset in the state space and the measurement space, where the DPF representing constraints is created. An information fusion scheme has been designed for DPFs, which are obtained from multisensor measurements and constraints. KITTI and self-collected sequences have been used in experiments, during which it is observed that the rotational drift is corrected and translational errors are reduced, thanks to the fusion of stereo visual odometry (SVO), heading measurements, and road maps. Note to Practitioners-Pose estimation aims to obtain ground vehicle's position and heading in a certain coordinate system. The multisensor fusion has been a popular solution in reducing estimation errors, and constraints are helpful in improving the pose estimation performance by limiting possible solutions. This article proposes a framework to model multisensor pose estimation problems with constraints. The approximated estimation scheme inspired by the Monte Carlo method has been provided such that the framework can be applied to various systems without analytic modeling. Experiments in KITTI and self-collected sequences have been conducted to demonstrate the superiority of the proposed approach by fusing stereo visual odometry (SVO) and heading measurements under road constraints. The proposed approach can be ameliorated by adding an absolute reference in translation to correct the inherent translational drift in VO.

关键词： Pose estimation Mathematical model roads Current measurement Land vehicles Extraterrestrial measurements Autonomous vehicles dynamic potential field (DPF) pose estimation road constraints sensor fusion

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road Constrained Monocular Visual Localization Using Gaussian-Gaussian Cloud Model

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2017年第12期18卷 3449-3456页

作者： Yang, Shuai Jiang, Rui Wang, Han Ge, Shuzhi Sam Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Natl Univ Singapore Dept Elect & Comp Engn Singapore 117583 Singapore

There are two main challenges, drift and scale ambiguity, restricting monocular visual odometry from an extensive application on real autonomous navigation. In this paper, an iterative localization framework is presented to globally localize a mobile vehicle equipped with a single camera and a freely available digital map. Inspired by the concept of cloud, a new Gaussian-Gaussian Cloud model is proposed to give a unified representation of the measurement randomness and scale ambiguity in monocular visual odometry. In this model, a collection of cloud drops is generated. Both the drift and scale ambiguity are considered and represented simultaneously in each cloud drop. To reduce the measurement uncertainties of any drop in Gaussian-Gaussian Cloud, road constraints from the open source map-OpenStreetMap-are utilized. The map is first converted to a template edge map and a shape matching step is then implemented to assign the probability of each cloud drop, indicating to what degree the drop accords with road constraints. A parameter estimation scheme is used to narrow down the scale ambiguity of monocular visual odometry while resampling cloud drops. Evaluations on the KITTI benchmark data set and our self-collected data set have demonstrated the stability and accuracy of the proposed approach.

关键词： road constraints monocular visual odometry (MVO) localization cloud model

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Complex Motion Modeling and State Estimation in road Coordinates

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Journal of Harbin Institute of Technology(New Series) 2017年第1期24卷 19-25页

作者： Keyi Li Xi Chen Gongjian Zhou School of Electronics and Information Engineering Harbin Institute of TechnologyHarbin 150001China

Constrained modeling and state estimation have attracted much attention in recent years. This paper focuses on target motion modeling and tracking in road coordinates. An improved initialization method,which uses the optimal fusion of the position measurements in different directions,is presented for the constraint coordinate Kalman filter(CCKF). The CCKF is evaluated with a comprehensive comparison to the state-of-art linear equality constraint estimation methods. Numerical simulation results demonstrate the better performance of the CCKF. Then the interacting multiple model CCKF(IMM-CCKF) is proposed to manifest the advantages of the CCKF in complex motion modeling and state estimations. The effectiveness of the IMM-CCKF in maneuvering target tracking with spatial equality constraints is demonstrated by numerical experiments.

关键词： Ground Targets Motion modeling road constraints Initialization IMM

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Nonlinear constrained tracking of targets on roads

Nonlinear constrained tracking of targets on roads

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7th International Conference on Information Fusion (FUSION)

作者： Yang, C Bakich, M Blasch, E Sigtem Technol Inc Harleysville PA 19438 USA

ISBN: (纸本)0780392868

Ground targets are constrained to move on the earth's surface and are most likely to travel along a road network. For targets on road, their interaction with the environment and with each other particularly at intersections are more structured, thus useful to tracking algorithms. Indeed, the knowledge of terrain database and road maps can be used as constraints and incorporated into the tracking algorithms. In this paper, we set forth a nonlinear formulation of tracking multiple interacting targets along road networks and apply nonlinear filtering techniques (namely, the extended Kalman filter, the unscented Kalman filter, the particle filter, and a hybrid Kalman particle filter) to the problem for such scenarios as air-to-ground surveillance. Simulation results are present to illustrate the performance of the nonlinear filters with the nonlinear formulation as compared to conventional ones.

关键词： ground targets road constraints tracking nonlinear filters EKF UKF/SPKF HKPF

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Multimodal Perception and Secure State Estimation for Robotic Mobility Platforms 1

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2022年

作者： Xinghua Liu Rui Jiang Badong Chen Shuzhi Sam Ge

Multimodal Perception and Secure State Estimation for Robotic Mobility Platforms Enables readers to understand important new trends in multimodal perception for mobile robotics This book provides a novel perspective o... 详细信息

ISBN: (数字)9781119876045

ISBN: (纸本)9781119876014

关键词： State estimation pose estimation Kalman filter particle filter attacks robotics mobile robots sensor fusion road constraints cloud models geometric pose estimation framework unified fusion scheme self-driving cars autonomous vehicles

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A multi-sensor-system cooperative scheduling method for ground area detection and target tracking

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Frontiers of Information Technology & Electronic Engineering 2023年第2期24卷 245-258页

作者： Yunpu ZHANG Qiang FU Ganlin SHAN Department of Electronic and Optical Engineering Shijiazhuang CampusArmy Engineering UniversityShijiazhuang050003China

A multi-sensor-system cooperative scheduling method for multi-task collaboration is proposed in this *** studied the method for application in ground area detection and target *** aim of sensor scheduling is to select the optimal sensors to complete the assigned combat tasks and obtain the best combat ***,an area detection model was built,and the method of calculating the detection risk was proposed to quantify the detection benefits in ***,combining the information on road constraints and the Doppler blind zone,a ground target tracking model was established,in which the posterior Carmér-Rao lower bound was applied to evaluate future tracking ***,an objective function was developed which considers the requirements of detection,tracking,and energy consumption *** solving the objective function,the optimal sensor-scheduling scheme can be *** results showed that the proposed sensor-scheduling method can select suitable sensors to complete the required combat tasks,and provide good performance in terms of area detection,target tracking,and energy consumption control.

关键词： Sensor scheduling Area detection Target tracking road constraints Doppler blind zone

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Research on distribution route with time window and on-board constraint based on tabu search algorithm

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EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2019年第1期2019卷 1页

作者： Ma, Chenglin Yang, Yanyan Wang, Lihai Chu, Chu Ma, Chao An, Lihua Northeast Forestry Univ NEFU Coll Engn & Technol Hexing Rd Harbin Heilongjiang Peoples R China

In order to solve the problem of the optimization of delivery and pickup cargoes' routes with time windows under the constraints of load and road, the method and algorithm were designed and researched based on these factors. Firstly, the model was built with the constraints of truck number, load quality, load capacity, maximum distance, and customer service time in order to minimize the transportation cost and time cost. Then, the Floyd Algorithm was used to determine the moving path and the shortest distance between each point with the road constraint. 0-1 integer programming method was used to determine the number and type of vehicles. Tabu search algorithm was used to determine the order of delivery and pickup points and the distribution route based on the influence of job requirements of pickup cargoes, the time cost, and the transportation cost. Finally, the case was given to verify the effectiveness of the proposed method. This method can be used to improve the efficiency of delivery and pickup cargoes and the level of distribution service.

关键词： Tabu search algorithm Time window Distribution path planning road constraints

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