A survey of localization in wireless sensor network

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

A Hybrid Indoor Location Positioning System

Indoor location positioning techniques have experienced impressive growth in recent years. A wide range of indoor positioning algorithms has been developed for various applications. In this work a practical indoor location positioning technique is presented which utilizes off-the-shelf smartphones and low-cost Bluetooth Low Energy (BLE) nodes without any further infrastructure. The method includes coarse and fine modes of location positioning. In the coarse mode, the received signal strength (RSS) of the BLE nodes is used for location estimation while in the fine acoustic signals are utilized for accurate positioning. The system can achieve centimeter-level positioning accuracy in its fine mode. To enhance the system’s performance in noisy environments, two digital signal processing (DSP) algorithms of (a) band-pass filtering with audio pattern recognition and (b) linear frequency modulated chirp signal with matched filter are implemented. To increase the system’s robustness in dense multipath environments, a method using data clustering with sliding window is employed. The received signal strength of BLE nodes is used as an auxiliary positioning method to identify the non-line-of-sight (NLoS) propagation paths in the acoustic positioning mode. Experimental measurement results in an indoor area of 10 m2 indicate that the positioning error falls below 6 cm

Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation

The Internet of Things (IoT) has started to empower the future of many industrial and mass-market applications. Localization techniques are becoming key to add location context to IoT data without human perception and intervention. Meanwhile, the newly-emerged Low-Power Wide-Area Network (LPWAN) technologies have advantages such as long-range, low power consumption, low cost, massive connections, and the capability for communication in both indoor and outdoor areas. These features make LPWAN signals strong candidates for mass-market localization applications. However, there are various error sources that have limited localization performance by using such IoT signals. This paper reviews the IoT localization system through the following sequence: IoT localization system review -- localization data sources -- localization algorithms -- localization error sources and mitigation -- localization performance evaluation. Compared to the related surveys, this paper has a more comprehensive and state-of-the-art review on IoT localization methods, an original review on IoT localization error sources and mitigation, an original review on IoT localization performance evaluation, and a more comprehensive review of IoT localization applications, opportunities, and challenges. Thus, this survey provides comprehensive guidance for peers who are interested in enabling localization ability in the existing IoT systems, using IoT systems for localization, or integrating IoT signals with the existing localization sensors

A New RSSI-based Centroid Localization Algorithm by Use of Virtual Reference Tags

A good design of node location is critical for efficient and effective wireless communications. This paper presents an improved algorithm, in order to solve the low localization accuracy caused by traditional centroid algorithm. The improved algorithm combined with VIRE system and traditional centroid algorithm. The VIRE algorithm is introduced and the signal propagation model is utilized to construct virtual reference tags in the location area. Simulation shows that this further developed algorithm has further improved the accuracy of positioning up to 35.12% compared to the traditional centroid algorithm. It is concluded that this algorithm can further improve the locating accuracy in comparison with the original centroid algorithm

When the Industry Goes Wireless: Drivers, Requirements, Technology and Future Trends

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