Abstract
Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network.
Highlights
Due to the availability of such low energy cost sensors, microprocessor, and radio frequency circuitry for information transmission, there is a wide and rapid diffusion of wireless sensor network (WSN)
While the Global Positioning System (GPS) is one of the most popular positioning technologies which is widely accessible, the weakness of high cost and energy consuming makes it different to install in every node
WSN is composed of a large number of inexpensive nodes that are densely deployed in a region of interests to measure certain phenomenon
Summary
Due to the availability of such low energy cost sensors, microprocessor, and radio frequency circuitry for information transmission, there is a wide and rapid diffusion of wireless sensor network (WSN). Node self-localization can be classified into two categories: range-based localization and rangefree localization The former method uses the measured the distance/angle to estimate the location. Previous works have been proposed to try to estimate the location of the single source in wireless binary sensor network (WBSN). A subtract on negative add on positive (SNAP) [20] algorithm was proposed to identify the source location using the binary sensor networks This is a fault-tolerant algorithm that is slightly less accurate but it is computationally less demanding in comparison with maximum likelihood estimation. In [21], the authors proposed a trust index based subtract on negative add on positive (TISNAP) method to improve the accuracy of localization for multiple event source localization This algorithm reduces the impact of faulty nodes on the source localization by decreasing their trust index.
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