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Designing a scheme for tracking an object in a wireless sensor network is a challenging job. In this paper, we propose a scheme for tracking a moving object in a wireless sensor network. The proposed scheme is based on dynamically computing the locations of the object by sensors that are lying in its communication range. Extensive simulations are carried out to evaluate the performance of the proposed...
A novel efficient method is proposed for the splitting and merging problems of track initiation, an important issue of multiple target tracking. Tack initiation demands that the method should determine the existence and initial state of a target quickly and correctly. There is no doubt that the high density of clutters (false alarm), large measurement errors and missing measurements deteriorate and...
In this paper, we propose a multi-object detection and tracking method using depth cameras. Depth maps are very noisy and obscure in object detection. We first propose a region-based method to suppress high magnitude noise which cannot be filtered using spatial filters. Second, the proposed method detect Region of Interests by temporal learning which are then tracked using weighted graph-based approach...
We consider a task prioritization problem of an active sonar tracking system when available ping resources may not be sufficient to sustain all tracking tasks at any particular time. In this problem, the time-varying conditions of a tracking task are represented by a finite-state discrete-time Markov decision process. The objective is to find a policy which decides at each time interval which tracking...
In this paper, we investigate the problem of bilinear control of a solar collector plant using the available boundary and solar irradiance measurements. The solar collector is described by a first-order 1D hyperbolic partial differential equation where the pump volumetric flow rate acts as the plant control input. By combining a boundary state observer and an internal energy-based control law, a nonlinear...
Distributed particle filters are appealing for cooperative tracking in distributed systems. However, a non-negligible amount of communication overhead can be required to synchronize the particle weights between agents. This paper proposes a particle weight approximation method, based on clustering and a smoothness assumption on the particle cloud distribution, to reduce the communication overhead...
Acoustic wave based underwater wireless sensor networks (UWSNs), generally deployed for underwater surveillance, face high challenges while meeting the demand for fast detection and tracking of many modern high-speed submerged intruders. The higher propagation speed of radio frequency (RF) wave keeps the RF based underwater networks into focus for supporting such fast detection requirements. In light...
In this paper, we propose a distributed simultaneous localization and tracking (SLAT) algorithm in wireless sensor networks. Belief propagation (BP) algorithm is applied on the factor graph which represents the factorization of the joint posterior distribution function. Due to the nonlinearity between the observations and location variables, closed-form expression of messages cannot be obtained by...
A Random Finite Set (RFS) based multi-target filter using a mixture of multi-object Dirac Delta and Poisson RFSs is proposed. The resulting distribution is closed under the Chapman-Kolmogorov equation while also being a conjugate prior to the “natural” multi-target likelihood function. A filtering algorithm is presented which efficiently extracts the highest weight components of the complete mixture...
We present the latest advances of our Canine Augmentation Technology (CAT) system. Our new approach to Urban Search and Rescue canine search sensing involves the use of stabilized and stitched multi-camera views and produces panoramic video that can be further processed for better human understanding. We discuss our initial results, some of the outstanding challenges and the existing and possible...
AR.Drone is a quadcopter with onboard sensors including a frontal camera. The drone can be controlled from a computer via WiFi. This paper describes a method for autonomous tracking of a selected object by AR.Drone. We utilize a computer-vision approach called tracking-learning-detection (TLD) to track an arbitrary object selected by a user in the video-stream going from the front camera of the drone...
In this paper we carried out designing and implementing of a target tracking data fusion algorithm based on a two stages graph solution using the computational model Gamma (General Abstract Model for Multiset mAnipulation). The proposed solution is the first parallel implementation of the method PPTS (Pairs of Plots in Two Stages). For this, we employed three Gamma implementations, where two of them...
Homotopy particle filters (HPFs), recently developed by Daum and Huang [1], present an alternative nonlinear filtering approach to sampling-based particle filters. Homotopy filters perform information update using the flow of particles to regions with high measurement likelihood. The particle flows in HPFs are solutions to a Fokker-Plank equation governing the dynamics of the posterior density function...
In this paper, we present a method to estimate the quality (trustfulness) of the solutions of the classical optimal data association (DA) problem associated with a given source of information (also called a criterion). We also present a method to solve the multi-criteria DA problem and to estimate the quality of its solution. Our approach is new and mixes classical algorithms (typically Murty's approach...
Modern sensors that are increasingly flexible may be used to schedule various functions. Such sensors typically have competing demands on limited sensor resources such as the sensor timeline. Sensor management systems attempt to meet the overall goal of the sensor user by considering the user's priorities and the capabilities of the sensor. This paper describes an algorithm for scheduling an electronically...
This paper proposes two track fusion methodologies for challenging multi-target tracking (MTT) settings where sensors have highly disparate characteristics and target density is high, leading to many competing tracking solutions. Though distributed multiple hypothesis tracking (MHT) is known to provide a viable solution paradigm, its applicability is limited to medium-size scenarios due to the need...
The tracking of space objects poses unique challenges when compared to traditional applications. Direct application of standard multi-target tracking models fails to yield accurate results for the case of space objects. For example, dynamic models for traditional applications require simple, often linear, discrete-time models. This is not the case for space objects where motion is nonlinear and computation...
We propose a method for multisensor-multitarget tracking with excellent scalability in the number of targets (which is assumed known), the number of sensors, and the number of measurements per sensor. Our method employs belief propagation based on a “detailed” factor graph that involves both target-related and measurement-related association variables. Using this approach, an increase in the number...
The use of random matrices for tracking extended objects has received high attention in recent years. It is an efficient approach for tracking objects that give rise to more than one measurement per time step. In this paper, the concept of random matrices is used to track surface vessels using highresolution automotive radar sensors. Since the radar also receives a large number of clutter measurements...
Joint target tracking and classification is a challenging problem where the class of a target must be estimated in addition to its kinematic states, such as position and velocity. This problem is of special importance both in civilian and in military domain, where target classification plays an important role in the decisions that an operator makes. Moreover, when several sensing options are available...
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