Paper
1 October 1990 PASSDAT: passive sensor data association for tracking - a PC software
Somnath Deb
Author Affiliations +
Abstract
This paper describes a PC software package for the following problem : We are given multiple passive sensors, each with a number of detections at a given time. With each detection, there is an associated line-of-sight measurement originating from a source. The source can be either a real target, in which case the measurements are azimuth and elevation angles of the target, plus some measurement noise, or a spurious one, i.e., a false alarm. Position estimates of targets can be formed by associating measurements originating from it. Mathematically, the measurement-target association problem leads to a generalized assignment problem. The problem of forming position estimates of multiple targets in a dense cluster, from passive sensor measurements at a given time, require at least three sensors. However, for three sensors, the three-dimensional assignment is known to be NP-complete, i.e., the complexity of the optimal algorithm increases exponentially with the size of the problem. The association problem is solved as a maximum likelihood estimation procedure; the likelihood function is maximized through the use of a near-optimal, iterative, and polynomial-time three dimensional assignment algorithm which employs Lagrangian relaxation technique that successively solves a series of (polynomial time) generalized two-dimensional assignment subproblems. The algorithm is coded in Fortran and available as an interactive PC software package PASSDAT. In this paper we present performance results and graphical scenario description of a representative test case solved by PASSDAT.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Somnath Deb "PASSDAT: passive sensor data association for tracking - a PC software", Proc. SPIE 1305, Signal and Data Processing of Small Targets 1990, (1 October 1990); https://doi.org/10.1117/12.2321769
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Cited by 5 scholarly publications.
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KEYWORDS
Sensors

Detection and tracking algorithms

Signal processing

3D acquisition

Data processing

Target detection

Passive sensors

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