Track Fusion with Road Constraints

Abstract

This paper is concerned with tracking of ground targets on roads and investigates possible ways to improve target state estimation via fusing a target's track with information about a road along which the target is believed to be traveling. A target track is estimated by a surveillance radar whereas a digital map provides the road network of a region under surveillance. When the information about roads is as accurate as (or even better than) radar measurements, it is desired naturally to incorporate such information (fusion) into target state estimation. In this paper, roads are modeled with analytic functions and its fusion with a target track is cast as linear or nonlinear state constraints in an optimization procedure. The constrained optimization is then solved with the Lagrangian multiplier, leading to a closed-form solution for linear constraints and an iterative solution for nonlinear constraints. Geometric interpretations of the solutions are provided for simple cases. Computer simulation results are presented to illustrate the algorithms.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2007
Accession Number
ADA520954

Entities

People

  • Chun Yang
  • Erik Blasch

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Coordinate Systems
  • Covariance
  • Estimators
  • Filters
  • Geographic Information Systems
  • Information Processing
  • Information Science
  • Information Systems
  • Kalman Filters
  • Measurement
  • Optimal Estimators
  • Roads
  • Simulations
  • Target Tracking
  • Trajectories
  • Vehicles

Readers

  • Calculus or Mathematical Analysis
  • Distributed Systems and Data Platform Development