Thursday, December 5, 2019

Fusion Architectures and Algorithms †Free Samples to Students

Question: Discuss about the Fusion Architectures and Algorithms. Answer: Introduction: Target tracking is the matter of concern for the current era as it is helpful to detect and monitor the motion of mobile targets. The sensor nodes consist of intelligence, where data can be processes while it flows across the network. Sensor networks comprise of current technologies such as power supply sub-system, sensing subsystem, a communication subsystem and computing subsystem. Target tracking is an application of WSN where sensor nodes control and report positions of moving elements of users with minimum latency. Thus it develops communication, production and quality of life [8]. It saves more lives, fuel, energies, resources and money though its real-life implementations in battlefield surveillance, gas leakage, wildlife monitoring, fire spread and detection of illegal border-crossing. Arnold, Shaw and Pasternack (2008) showed that open researches for applications of target tracking include dealing with varying speeds and direction changes of moving of moving objects. Further, the technology is useful to recover energy effective missing target track, comparison of the performance of dynamic and target track [9] [12]. Moreover, it is useful to find a relationship between consumption of energy with forming cluster and tracking, provisioning and predicting accuracy [4]. Target tracking is also applicable foe designing well organized nominal and computing transmission of messages instead of degradation of performance since transmission of message consumes lots of energy as discussed by Li and Jilkov (2003). Lastly, the sensor nodes are helpful for fault detection. As seen from the above approaches, it can be deduced that energy conservation maximizes the network lifetime and is addressed via effective, dependable wireless communication [3] [14]. Hence, Blackman (2004) highlighted the presence of intelligent placement of sensors for gaining sufficient coverage, security and smart storage management [10] [13]. This is done through data compression and data aggregation. The approaches are meant for satisfying energy constraint and provide quality of service for those applications [6]. As per as reliable communications are concerned, Mazor (2007) reveals that services like packet-loss recovery, acknowledgements, active buffer monitoring and congestion control are needed to ensure guaranteed packet delivery [5]. However, energy consumption is a primary concern under target tracking protocols. Vermaak, Godsill and Perez (2005) analyzed that while the sensor nodes face energy depletion, it dies and gets disconnected from networks significantly affecting the application and the performance [15]. Some of the limitations reviewed by Bar-Shalom and Birmiwal (2002) and Zhang and Cao (2004) are listed hereafter [7] [11]. A lifetime of sensor networks depends on the number of active nodes and network connectivity of the net. Hence, energy should be utilized for maximizing the lifetime of the network. Further, it is unable to track targets smart as the number of goals become huge. Besides, target tracking needs modifications in real time. Detected object is larger than the actual size. Various holes are present in the results of detection. While the objects move slowly, the motion is unreliable. Huge blocks fail to match the real motion sequence. References: "Efficient target tracking using dynamic programming - IEEE Journals Magazine",Ieeexplore.ieee.org, 2018. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/249112/. [Accessed: 12- Apr- 2018]. "Survey of maneuvering target tracking. Part I. Dynamic models - IEEE Journals Magazine",Ieeexplore.ieee.org, 2018. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/1261132/. [Accessed: 12- Apr- 2018]. "Multiple hypothesis tracking for multiple target tracking - IEEE Journals Magazine",Ieeexplore.ieee.org, 2018. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/1263228/. [Accessed: 12- Apr- 2018]. "Interacting multiple model methods in target tracking: a survey - IEEE Journals Magazine",Ieeexplore.ieee.org, 2018. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/640267/. [Accessed: 12- Apr- 2018]. "Moving target classification and tracking from real-time video - IEEE Conference Publication",Ieeexplore.ieee.org, 2018. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/732851/. [Accessed: 12- Apr- 2018]. "Variable Dimension Filter for Maneuvering Target Tracking - IEEE Journals Magazine",Ieeexplore.ieee.org, 2018. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/4102704/. [Accessed: 12- Apr- 2018]. "DCTC: dynamic convoy tree-based collaboration for target tracking in sensor networks - IEEE Journals Magazine",Ieeexplore.ieee.org, 2018. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/1343904/. [Accessed: 12- Apr- 2018]. "Dynamic clustering for acoustic target tracking in wireless sensor networks - IEEE Journals Magazine",Ieeexplore.ieee.org, 2018. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/1318595/. [Accessed: 12- Apr- 2018]. "Survey of maneuvering target tracking. Part V. Multiple-model methods - IEEE Journals Magazine",Ieeexplore.ieee.org, 2018. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/1561886/. [Accessed: 12- Apr- 2018]. "Sequential Monte Carlo methods for multiple target tracking and data fusion - IEEE Journals Magazine",Ieeexplore.ieee.org, 2018. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/978386/. [Accessed: 12- Apr- 2018]. "Stable multi-target tracking in real-time surveillance video - IEEE Conference Publication",Ieeexplore.ieee.org, 2018. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/5995667/. [Accessed: 12- Apr- 2018]. "You'll never walk alone: Modeling social behavior for multi-target tracking - IEEE Conference Publication",Ieeexplore.ieee.org, 2018. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/5459260/. [Accessed: 12- Apr- 2018]. "Distributed fusion architectures and algorithms for target tracking - IEEE Journals Magazine",Ieeexplore.ieee.org, 2018. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/554211/. [Accessed: 12- Apr- 2018]. "Observability of target tracking with bearings-only measurements - IEEE Journals Magazine",Ieeexplore.ieee.org, 2018. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/543868/. [Accessed: 12- Apr- 2018]. "Multi-target tracking using joint probabilistic data association - IEEE Conference Publication",Ieeexplore.ieee.org, 2018. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/4046781/. [Accessed: 12- Apr- 2018].

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