Multitarget Tracking Using Multiple Bistatic Range Measurements with Probability Hypothesis Densities

نویسندگان

  • Martin Tobias
  • Aaron D. Lanterman
چکیده

Ronald Mahler’s Probability Hypothesis Density (PHD) provides a promising framework for the passive coherent location of targets observed via multiple bistatic radar measurements. We consider tracking targets using only range measurements from a simple non-directional receiver that exploits non-cooperative FM radio transmitters as its “illuminators of opportunity.” A target cannot be located at a single point by a particular transmitter-receiver pair, but rather it is located along a bistatic range ellipse determined by the position of the target relative to the receiver and transmitter. Target location is resolved by using multiple transmitter-receiver pairs and locating the target at the intersection of the resulting bistatic ellipses. Determining the intersection of these bistatic range ellipses and resolving the resultant ghost targets is generally a complex task. However, the PHD provides a convenient and simple means of fusing together the multiple range measurements to locate targets. We incorporate signal-to-noise ratios, probabilities of detection and false alarm, and bistatic range variances into our simulation.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Probability Hypothesis Density-Based Multitarget Tracking With Bistatic Range and Doppler Observations

Ronald Mahler’s Probability Hypothesis Density (PHD) provides a promising framework for the passive coherent location of targets observed via multiple bistatic radar measurements. We apply a particle filter implementation of the Bayesian PHD filter to target tracking using both range and Doppler measurements from a simple non-directional receiver that exploits non-coöperative FM radio transmitt...

متن کامل

Bayesian Multiple Target Tracking in Forward Scan Sonar Images Using the PHD Filter

A multiple target tracking algorithm for forward-looking sonar images is presented. The algorithm will track a variable number of targets estimating both the number of targets and their locations. Targets are tracked from range and bearing measurements by estimating the first-order statistical moment of the multitarget probability distribution called the Probability Hypothesis Density (PHD). Th...

متن کامل

Multitarget Tracking Using a Particle Filter Representation of the Joint Multitarget Density

This paper addresses the problem of tracking multiple moving targets by recursively estimating the joint multitarget probability density (JMPD). Estimation of the JMPD is done in a Bayesian framework and provides a method for tracking multiple targets which allows nonlinear target motion and measurement to state coupling as well as non-Gaussian target state densities. The JMPD technique simulta...

متن کامل

A shrinkage probability hypothesis density filter for multitarget tracking

In radar systems, tracking targets in low signal-to-noise ratio (SNR) environments is a very important task. There are some algorithms designed for multitarget tracking. Their performances, however, are not satisfactory in low SNR environments. Track-before-detect (TBD) algorithms have been developed as a class of improved methods for tracking in low SNR environments. However, multitarget TBD i...

متن کامل

A New Pruning/merging Algorithm for Mht Multitarget Tracking

In this paper we develop a new general Viterbi algorithm for multitarget tracking. A standard Multiple Hypothesis Tracking (MHT) formulation, based on Maximum A Posterior (MAP) estimation, is considered for optimally associating measurement data over time to form estimates of the multiple tracks. For estimating K tracks, a trellis diagram of the measurements is used to depict all track set hypo...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004