Paper
16 August 2001 Multitarget tracking on intensity-modulated sensor data
Roy L. Streit, Marcus L. Graham, Michael J. Walsh
Author Affiliations +
Abstract
Tracking energy on an intensity-modulated sensor output typically requires windowing, thresholding, and/or interpolation to arrive at point measurements to feed the tracking algorithm. Conventional trackers are point trackers, and point measurement estimation procedures pose problems for tracking signal energy that is distributed across many sensor cells. Such signals are sometimes termed over-resolved. Large arrays provide greater resolution with the potential for improved detection and classification performance, but higher resolution is in direct conflict with tracking over-resolved signals. The Histogram-Probabilistic Multi-Hypothesis Tracker (H-PMHT) algorithm addresses these issues and provides a means for modeling and tracking signals that are spread across several contiguous sensor cells. H-PMHT models the cell responses as a received energy histogram, and the probability density underlying this histogram is modeled by a mixture density. Elements of the H-PMHT signal model, theory, and algorithm are presented for linear Gauss-Markov targets. Tracking examples using simulated azimuth beam data are presented.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Roy L. Streit, Marcus L. Graham, and Michael J. Walsh "Multitarget tracking on intensity-modulated sensor data", Proc. SPIE 4380, Signal Processing, Sensor Fusion, and Target Recognition X, (16 August 2001); https://doi.org/10.1117/12.436985
Lens.org Logo
CITATIONS
Cited by 3 scholarly publications and 1 patent.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Sensors

Detection and tracking algorithms

Data modeling

Matrices

Quantization

Digital filtering

Expectation maximization algorithms

Back to Top