Optimal Placement of Heterogeneous Sensors in Target Tracking

Abstract

Target tracking performance is determined by the fidelity of target mobility model (F, Q), tracking sensor measurement quality (R), and sensor-to-target geometry (H). A tracking sensor manager has choices in sensor selection/placement (H), waveform design (R), and filter tuning (F and Q), thus affecting the tracking performance in many ways. This paper concerns with the geometry aspect of sensor placement so as to optimize the tracking performance. Recently, a considerable amount of work has been published on optimal conditions for instantaneous placement of homogeneous sensors (same type and same measurement quality) in which the targets are either assumed perfectly known or the target location uncertainty is averaged out via the expected value of the determinant of the Fisher information matrix. In this paper, we derive conditions for optimal placement of heterogeneous sensors based on maximization of the updated Fisher information matrix from an arbitrary prior characterizing the uncertainty about the initial target location. The heterogeneous sensors can be of the same or different types (ranging sensors, bearing-only sensors, or both). The sensors can also make, over several time steps, multiple independent measurements of different qualities.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2011
Accession Number
ADA565897

Entities

People

  • Chun Yang
  • Erik Blasch
  • Lance Kaplan
  • Michael Bakich

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Coordinate Systems
  • Covariance
  • Detectors
  • Eigenvalues
  • Equations
  • Errors
  • Estimators
  • Geometry
  • Measurement
  • Military Research
  • Observation
  • Orientation (Direction)
  • Range Finding
  • Target Tracking
  • Two Dimensional
  • Uncertainty

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Sensor Fusion and Tracking Systems.