Multi-Target/Multi-Sensor Tracking using Only Range and Doppler Measurements

Abstract

A new approach is described for combining range and Doppler data from multiple radar platforms to perform multi-target detection and tracking. In particular, azimuthal measurements are assumed to be either coarse or unavailable, so that multiple sensors are required to triangulate target tracks using range and Doppler measurements only. Increasing the number of sensors can cause data association by conventional means to become impractical due to combinatorial complexity, i.e., an exponential increase in the number of mappings between signatures and target models. In the new approach, the data association is performed probabilistically, using a variation of expectation-maximization (EM). Combinatorial complexity is avoided by performing an efficient optimization in the space of all target tracks and mappings between tracks and data. The full, multi-sensor, version of the algorithm is tested on simulated data. The results demonstrate that accurate tracks can be estimated by exploiting spatial diversity in the sensor locations. These results are promising, and demonstrate robustness in the presence of nonhomogeneous clutter.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2009
Accession Number
ADA506413

Entities

People

  • John Schindler
  • Leonid Perlovsky
  • Ross Deming

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Computational Complexity
  • Data Association
  • Detection
  • Information Operations
  • Mathematical Models
  • Military Research
  • Multiple Hypothesis Tracking
  • Multitarget Tracking
  • Probability
  • Sequential Monte Carlo Methods
  • Target Signatures
  • Target Tracking
  • Time Intervals
  • Two Dimensional

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Vision.
  • Distributed Systems and Data Platform Development

Technology Areas

  • Space
  • Space - Space Objects