RSSI-Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers

Paul, Anindya S.; Wan, Eric A.

doi:10.1109/jstsp.2009.2032309

Cited by 244 publications

(113 citation statements)

References 38 publications

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“…Kalman filter is a typical one, which consists of 2 steps as estimation and measurement [9]. But it has several flaws, especially the computation cost due to high sample rate.…”

Section: Motion Enginementioning

confidence: 99%

A Wireless Sensor Network based Indoor Localization System for Emergency Application Use

Tang¹,

Zhang²,

Feng³

et al. 2017

Proceedings of the 2017 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2017)

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Abstract. Every year, tragedy of indoor emergency accidents lead to immeasurable loss to families, bringing the society great shocks. This is mainly due to the harsh environment of emergency accidents, like firefighting, as the on-fire buildings are usually full of smoke and danger. One of the most directional issues is localization, as it is almost impossible to find the person trapped in the building without knowing the location. Localization is not only critical for evacuees seeking help from outside, but also important for self-evacuation. But unfortunately, a reliable and applicable indoor localization system is not available today, because of accuracy, cost and efficiency. In this paper, we present a novel localization system, which combines pedestrian reckon algorithm with wireless sensor network, hence providing an automatic and reliable solution towards this issue.

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“…Kalman filter is a typical one, which consists of 2 steps as estimation and measurement [9]. But it has several flaws, especially the computation cost due to high sample rate.…”

Section: Motion Enginementioning

confidence: 99%

A Wireless Sensor Network based Indoor Localization System for Emergency Application Use

Tang¹,

Zhang²,

Feng³

et al. 2017

Proceedings of the 2017 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2017)

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“…The "too complex" argument is also applicable to the work of [12] which uses Sigma-Point Kalman Smoothers; to the work of [4] which uses a centralized server to solve individual devices' log-distance path loss equations and runs a genetic algorithm. The work of [18] proposes a combination of metrics for distance estimation and localization and uses four distinct metrics to represent a better model of the short and long-term quality of the link as well as information on the dynamic variation and the trend of the communication signal.…”

Section: Related Workmentioning

confidence: 99%

“…Additional environmental factors such as temperature and humidity have been shown to interfere with RSSI readings as well [11]. So due to a strong non-linear characteristic of RSSI, any localization or distance estimation method that relies on previously measured RSSI fingerprint levels, may fail even for approaches that apply filters or signal processing [12][13][14]. Comprehensive studies of indoor RSSI have been conducted in [10,15] where the authors show that the only way to improve the accuracy would be through a more complex model of the RSSI behavior.…”

Section: Introductionmentioning

confidence: 99%

Accurate Distance Estimation Using Fuzzy based combined RSSI/LQI Values in an Indoor Scenario: Experimental Verification

Oliveira¹,

Raju²,

Agrawal³

2012

NPA

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The received signal strength indicator (RSSI) and the link quality indicator (LQI) are the metrics that are commonly available in commercial off-the-shelf (COTS) sensor hardware. The former has been widely regarded as the main source for distance estimation and node localization. However, experimentally RSSI has been shown to behave in an inconsistent manner, even in ideal scenarios, and serve at best as bounds for distances. The latter is effectively a measure of chip error rate, and can be used to identify higher quality transmissions, and the combination RSSI/LQI can be expected to make more precise estimates with the tradeoff of increased delay and estimation cost. In this paper, we describe our distance estimation system that uses these two metrics and test our hypothesis purely through experimental measurements using sensor nodes. Results indicate that such a combination of metrics can be used to provide a tighter bound on the range of estimated distances. We then quantify the improvement in distance estimation by relying on these two metrics. Through a unique classification using fuzzy logic and TBM, we developed an algorithm that is capable of precise distance estimation within the range of 100cm to 400cm, on at least 80% of the times while reaching accuracy as high as 100%.

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“…Each technique is based on a certain signal parameter being measured. The most common of these signal parameters are the angle of arrival (AOA) [4], time of arrival (TOA) [5], time difference of arrival (TDOA) [6], and the received signal strength (RSS) [7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Real Time RSS Based Adaptive Beam Steering Algorithm for Autonomous Vehicles

Ibrahim¹,

Sharawi²

2014

PIER C

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Abstract-A real time, low complexity algorithm is developed to steer a planar patch antenna array beam to the maximum received signal strength (RSS) direction for communication link enhancement. The beam steering towards the maximum incoming signal direction is based on an iterative technique utilizing a set of RSS measurements taken from specific locations in the search space, these locations collectively form an ellipse. The algorithm is denoted as "elliptical peeking". It was simulated for a flying unmanned aerial vehicle (UAV) as the vehicle tries to identify the maximum signal strength incoming direction of a stationary ground signal and it was tested on an embedded platform to validate its low demand for computational power. Such an algorithm is suitable for autonomous platforms due to its simplicity and low cost.

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RSSI-Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers

Cited by 244 publications

References 38 publications

A Wireless Sensor Network based Indoor Localization System for Emergency Application Use

A Wireless Sensor Network based Indoor Localization System for Emergency Application Use

Accurate Distance Estimation Using Fuzzy based combined RSSI/LQI Values in an Indoor Scenario: Experimental Verification

Real Time RSS Based Adaptive Beam Steering Algorithm for Autonomous Vehicles

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