This paper addresses the density based multi-sensor cooperative fusion using random finite set (RFS) type multi-object densities (MODs). Existing methods use scalar weights to characterize relative information confidence among local MODs, and in this way portion of contribution each MOD fused global can be tuned via adjusting these weights. Our analysis shows that mechanism a coefficient oversimplified for practical scenarios, as an is complex usually space-varying due imperfection sensor...

In this paper, a network cost based node selection (NCBNS) strategy is proposed to address the problem for multiple target tracking (MTT) in netted radar system (NRS). NCBNS, we first establish model on clustering framework with both considering of scheduling and transmission. Herein, determined by select when forming cluster while transmission depends head (CH) specific cluster. Then, formulated as mathematical optimization minimizing constraints number requirement accuracy. It shown that...

In this paper, we address the joint sensor registration and multi-target tracking problem using PHD filter generalized Covariance Intersection (GCI) fusion rule. Each is assumed to have no knowledge about positions (referred as drift parameters) of its neighboring nodes in local coordinate system. our method, parameters are estimated first, then states obtained based on at each common global reference time step. The GCI divergence used measure degree discrepancy between multiple posterior...

This paper mainly addresses the dim target detection and tracking problems in multiple pulse repetition frequency (MPRF) radar system using multi-frame track-before-detect (MF-TBD) method. Generally, each measurement frame received by MPRF faces range Doppler ambiguities at specific (PRF) setting. We have proposed a multi-PRF TBD (MPMF-TBD) algorithm [1], which provides an energy-efficient solution to accomplish kinematic state estimation ambiguity resolution simultaneously. However, this...

In this paper, a multi-sensor control method with limited sensor field-of-view (FoV) based on Poisson multi-Bernoulli mixture (PMBM) filter is proposed, which provides solution to the multi-target joint search and tracking problem. First, we propose robust fusion for PMBM posterior densities FoV generalized covariance intersection (GCI) criterion. Then, cost function constructed fused density, takes into account both discovered undiscovered targets. The optimal scheme obtained by minimizing...

In this paper, a robust and high-accuracy decentral-ized fusion strategy is proposed for multi-target tracking (MTT) in netted radar systems with non-overlapping field of view (FoV). Each the network runs local Probability Hypothetical Density (PHD) filter decentralized consensus protocol to reduce communication bandwidth eliminate information inconsistency among nodes. above process, most critical core an effective strategy. Our method adopts geometric covariance intersection (GCI) rule...

A Markov chain model is constructed to simulate pattern formation arising from an evolutionary population of interactive homogeneous agents. In the structure optimal evolution and stochastic properties, exhibits emergent properties with rich dynamical diagrams. We study cluster splitting transition coarsening period-adding phenomena shown by model, which gives example in complex system reveals behavior process.

We construct a Markov process model to describe the evolution of labor division and its dynamical behavior is investigated by numerical simulations in detail. have shown that under mechanism increasing returns, will emerge from initial homogenous distribution with change parameters there are period-adding coarse-grained bifurcations model. The gives an example emergent property complex systems reveals interesting chain process. Key words: Evolution, Bifurcation, Pattern formation PACS...

The following topics are dealt with: radar signal processing; imaging; detection; Doppler radar; synthetic aperture object target tracking; clutter; array processing.

Compared with the probability hypothesis density (PHD) filter for sets of targets, trajectory (TPHD) can estimate trajectories in a principle way and has better target tracking performance. This paper aims at extending TPHD to distributed multitarget (MTT) multi-sensor system. However, set based fusion implementation, state difference phenomenon makes clustering merging techniques unfeasible space. To address this problem, studies space decomposition proposes MTT method on weighted...

This paper addresses the problem of distributed multi-target tracking (MTT) in a radar network wherein both positions and fields view (FoVs) each are unknown to network. The probability hypothesis density (PHD) filters running locally for MTT. Weighted Arithmetic Average (WAA) fusion rule is employed because its robustness multi-sensor with different FoVs. Due FoVs radars may be time-varying, our method, local intensity densities decomposed into number sub-densities by clustering algorithm....

This paper addresses the multi-sensor control problem for distributed multi-target tracking (DMTT) with limited sensor fields-of-view (FoVs). Existing methods cannot be directly used when FoVs of sensors are very limited. To solve this problem, we propose a new strategy that contains two key points. One is to generate FoV-based pseudo measurement set, which also sift through commands. The other one reward function composed Cauchy-Schwarz (CS) divergence between fused predicted density and...

This paper addresses the problem of maneuvering multi-target tracking by a network sensors having different and limited fields view (FoV s). Each local sensor runs Gaussian Mixture Probability Hypothetical Density (GMPHD) filter. Due to target maneuver, based on single motion model, severe performance degradation can be observed. We propose use multi-model (MM) method realize adaptation characteristic so as overcome maneuverability targets. Then considering FoV s in are limited, standard...