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Multilane Road Target Tracking Using Radar and Image Sensors

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Tracking of a maneuvering target moving on a multilane road using radar and image sensor based measurements is studied. A novel 2D road representation of an on-road moving target is introduced. A natural description of the target longitudinal and lateral maneuvering behavior in the 2D road coordinates is given using multiple models. An improved mean-adaptive acceleration model is utilized to describe the longitudinal maneuver modes of the motion. Three IMM-based estimators are developed that use different schemes for fusion of radar and image sensor based measurements: centralized, distributed, and sequential. Simulation results are presented that illustrate the performance of the proposed estimators and demonstrate their improved capability compared with a known 1D road coordinate (mileage) estimator. Furthermore, a Hidden Markov Model (HMM) formulation and two algorithms for lane-only
tracking using lane observations are proposed. A lane observation model is derived from a basic image sensor providing raw observation data. Simulation results show that the proposed HMM-based lane estimators can achieve good performance for lane tracking when only basic image sensor based measurements are available.

X. Rong Li

Field of Interest

“The field of interest shall be the organization, systems engineering, design, development, integration, and operation of complex systems for space, air, ocean, or ground environments. These systems include but are not limited to navigation, avionics, mobile electric power and electronics, radar, sonar, telemetry, military, law-enforcement, automatic test, simulators, and command and control."


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