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The paper addresses the problem of target-tracking in tactical military surveillance operations. More specifically, a closed-loop approach to adapt the sensing and tracking operations is proposed and compared to the conventional open-loop and static approach. The objective is to control and maintain, over a certain volume of interest and by way of clustering and scheduling strategies, the level of...
This paper discusses the application of holonic control paradigm to sensor management in military surveillance operations. Sensor management is described both as part of the data fusion process and as a control problem. The choice of holonic control as the most adequate architecture for sensor management in the military environment is explained and its application to surveillance operations illustrated...
In this paper, we propose a method of combining some interacting multiple model-extended Viterbi (IMM-EV) algorithms for target tracking. The objective of the proposed scheme is to take the maximum advantage of the combined strengths of some IMM-EV algorithms so as to achieve better performance and/or computational efficiency than the IMM and some tracking algorithms. Simulation results demonstrate...
Target tracking from incomplete measurements of distinct sensors in a sensor network is a task of data fusion, present in a lot of applications. Difficulties in tracking using extended Kalman filters lead to unstable behavior, mainly caused by difficult initialization. Instead of using numerical batch-estimators, we offer an analytical approach to initialize the filter from a minimum number of observations...
Errors due to sensor bias are often present in sensor data and can reduce the tracking accuracy and stability of multi-sensor systems. The other practical problem is that the target data reported by the sensors are usually not time-coincident or synchronous due to the different data. This paper deals with these problems and presents a new algorithm for estimation of both constant and dynamic biases...
Real radar data containing a small manoeuvring boat in sea clutter is processed using a grid based finite difference implementation of continuous-discrete filtering. Both two dimensional diffusion and four dimensional constant velocity models are implemented using Gaussian and Rayleigh sea clutter models. Superior performance is observed for the constant velocity model and significant sensitivity...
A dynamic image fusion scheme for infrared and visible sequence based on region target detection is proposed in this paper. Target detection technique is employed to segment the source images into target and background regions. Different fusion rules are adopted respectively in target and background regions. A limitedly redundant discrete wavelet transform (LR DWT) method is introduced to achieve...
Distributed Kalman filters are often used in multisensor target tracking where the fusion center receives local estimates and fuses them to obtain the global target state estimate. With such a fusion architecture, each local tracker can communicate less frequently with the fusion center than the local filter update rate. The global target state estimate via track fusion is usually less accurate than...
In this paper, we derive the updating formula of the cardinalized probability hypothesis density (CPHD) filter recently developed in the works of Mahler et al., (2006) from the non- Poisson multiple-hypothesis tracking (MHT) algorithm developed earlier in the works of Mori et al. (2004). The particular form of the CPHD updating formula developed in this paper is expressed only with the probability...
In military command & control applications, the information quality requirements are very context-dependent and seldom predefined. This leaves much room for adaptation. In this paper, the duration of the search & lock-on operations of the fire control radar is estimated and used as an adaptation trigger. The proposed estimation process aims at establishing a quantitative relationship between...
We seek to establish a quality metric for sensor fused video based on the performance of a multisensor system that actively tracks multiple surface targets over an extended field of regard Such a system must, in real-time, fuse multisensor/spectral imagery, detect targets reliably, track the targets for extended time periods as they move, stop, approach, cross, hide/emerge, over an extended field...
We describe data fusion technology relevant to two applications of potential benefit to the Canadian army. The first application is a local situational awareness system (LSAS) while the second is a versatile surveillance platform. The LSAS improves an armored vehicle crew's ability to recognize and locate threats and hazards without leaving the relative safety of their vehicle. It is designed primarily...
An algorithm is developed for joint tracking and detection of multiple maneuvering targets using a wireless sensor network. The target existence probability framework is adopted in which a collection of tentative tracks, each characterised by a posterior density and existence probability, is maintained. Track state posterior densities are approximated using the unscented Kalman filter and the interacting...
Many problems involve joint decision and estimation, where qualities of decision and estimation affect each other. This paper proposes an integrated approach based on a new Bayes risk, which is a generalization of those for decision and estimation separately. Theoretical results of the optimal joint decision and estimation that minimizes the new Bayes risk are presented. The power of the new approach...
The focus of wireless sensor networks is to develop low cost sensors with sufficient computing and communication capabilities to support networked sensing applications. The emphasis on lower cost led to sensors that are less accurate and less reliable than their wired sensor counterparts. Sensors usually suffer from both random and systematic (bias) problems. Even when the sensors are properly calibrated...
Sensor resource management (or process refinement) is a element of any information fusion system. Common level 4 sensor management (SM) inter-relations to level 1 target tracking and identification have been developed in the literature. During Fusion06, a panel discussion was held to explore the challenges and issues pertaining to the interaction between SM and situation and threat assessment. This...
The interacting multiple model filter has long been the preferred method to handle multiple models in target tracking. The filter finds a suboptimal solution to a problem, which implicitly assumes that immediate model shifts have the highest probability. We argue that this model-shift property does not capture the typical nature of maneuvering targets, namely that changes in target dynamics persist...
Underwater passive acoustic target tracking is challenging in littoral environments. One way to mitigate the difficulties is to add non-acoustic sensors and use data fusion. The topic of this paper is how to evaluate, in an objective way, the performance of data fusion in this application. Different performance measures are discussed. The performance measures are applied on data from a trial where...
In multi-sensor multi-target bearings-only tracking we often see false intersections of bearings known as ghosts. When the bearing measurements from each sensor have been associated to form sequences termed threads, the problem is to associate pairs of threads to identify the true target intersections. In this paper we present two algorithms: (i) classical bayesian thread association (CBTA) and (ii)...
An alternating directions method is presented for joint maximum a posteriori estimation of target track and sensor field using bistatic range data. The algorithm cycles over two sub-algorithms: one improves the target state estimate conditioned on sensor field state, and the other improves the sensor field state estimate conditioned on target state. Nonlinearities in the sub-algorithms are mitigated...
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