论文信息 - Traffic intensity estimation via PHD filtering

Traffic intensity estimation via PHD filtering

The paper will address the estimation of road traffic intensity from available measurements of mobile vehiclespsila coordinates. To this end, the work will jointly exploit PHD (probability hypothesis density) filtering techniques based on the so called particle filter approach and road-map information.

[1] R. Mahler. Multitarget Bayes filtering via first-order multitarget moments , 2003 .

[2] Ronald P. S. Mahler,et al. Statistical Multisource-Multitarget Information Fusion , 2007 .

[3] Yakov Bar-Shalom,et al. Multitarget-Multisensor Tracking: Principles and Techniques , 1995 .

[4] Alfred O. Hero,et al. Radar data processing: Vol. I-Introduction and tracking , 1986, IEEE Trans. Acoust. Speech Signal Process..

[5] A. Doucet,et al. Sequential Monte Carlo methods for multitarget filtering with random finite sets , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[7] Branko Ristic,et al. Beyond the Kalman Filter: Particle Filters for Tracking Applications , 2004 .

[8] Hung T. Nguyen,et al. An Introduction to Random Sets , 2006 .

[9] Ba-Ngu Vo,et al. The Gaussian Mixture Probability Hypothesis Density Filter , 2006, IEEE Transactions on Signal Processing.