Implementation of a Kalman Filter for Single-Sensor Tracking

Abstract

Bise research investigates the use of a single passive acoustic sensor for vehicle tracking. The sensor is part of a network of acoustic sensor arrays which the bearings-only measurements for the tracking process. The motion estimates from these deployed arrays are then fused at a gateway where an overall estimate is formed. Although tracking is performed with a single sensor the bearings-only tracking process is initially unobservable. Previous work L, 2 has shown that for sensors mounted on a moving platforms the process becomes observable after a maneuver. In this work initialization is performed using two triangulated sensors to invoke observability. One to three bearing measurements per sensor are used for the initialization process depending on the number of filter states to be initialized. The second sensor is then released and tracking performed on the initialized filter. The residual is monitored for filter divergence and consequently the need for filter re-initialization.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2000
Accession Number
ADA392196

Entities

People

  • James E. Whitney

Organizations

  • Morgan State University

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Cartesian Coordinates
  • Classification
  • Detectors
  • Dynamics
  • Equations
  • Estimators
  • Filters
  • Generators
  • Geometry
  • Kalman Filters
  • Low Noise
  • Maneuvers
  • Measurement
  • Passive Tracking
  • Simulations
  • Surveillance

Readers

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  • Sensor Fusion and Tracking Systems.