Track-Before-Detect Algorithm for Faint Moving Objects based on Random Sampling and Consensus

Abstract

There are many algorithms developed for tracking and detecting faint moving objects in congested backgrounds. One obvious application is detection of targets in images where each pixel corresponds to the received power in a particular location. In our application, a visible imager operated in stare mode observes geostationary objects as fixed, stars as moving and non-geostationary objects as drifting in the field of view. We would like to achieve high sensitivity detection of the drifters. The ability to improve SNR with track-before-detect (TBD) processing, where target information is collected and collated before the detection decision is made, allows respectable performance against dim moving objects. Generally, a TBD algorithm consists of a pre-processing stage that highlights potential targets and a temporal filtering stage. However, the algorithms that have been successfully demonstrated, e.g. Viterbi-based and Bayesian-based, demand formidable processing power and memory. We propose an algorithm that exploits the quasi constant velocity of objects, the predictability of the stellar clutter and the intrinsically low false alarm rate of detecting signature candidates in 3-D, based on an iterative method called "RANdom SAmple Consensus and one that can run real-time on a typical PC. The technique is tailored for searching objects with small telescopes in stare mode. Our RANSAC-MT (Moving Target) algorithm estimates parameters of a mathematical model (e.g., linear motion) from a set of observed data which contains a significant number of outliers while identifying inliers. In the pre-processing phase, candidate blobs were selected based on morphology and an intensity threshold that would normally generate unacceptable level of false alarms.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2014
Accession Number
ADA616722

Entities

People

  • Anthony Dentamaro
  • Phan Dao
  • Richard Rast
  • Stephen Gregory
  • Vincent Schmidt
  • Waid Schlaegel

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Artificial Satellites
  • Detection
  • Detectors
  • Elliptical Orbits
  • False Alarms
  • Geosynchronous Satellites
  • Low Earth Orbits
  • Mathematical Models
  • Moving Targets
  • Probability
  • Space Objects
  • Spacecraft
  • Statistical Samples
  • Statistical Sampling
  • Three Dimensional

Readers

  • Astronomy/Astrophysics
  • Computer Vision.
  • Radar Systems Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Space
  • Space - Space Objects