Enhanced calibration technique for RSSI-based ranging in body area networks

Blumrosen, Gaddi; Hod, Bracha; Anker, Tal; Dolev, Danny; Rubinsky, Boris

doi:10.1016/j.adhoc.2012.08.002

Cited by 30 publications

(23 citation statements)

References 17 publications

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“…10. The first echo is the one received at the moment of transmission directly from the speaker to the microphone, 10. Signal spectrogram for m'th pulse repetition for the experiment described in (Fig.…”

Section: A Pre-processingmentioning

confidence: 99%

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Noncontact Wideband Sonar for Human Activity Detection and Classification

2014

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This paper suggests using a wideband sonar system to detect and classify human activity in indoor environment. The high bandwidth enables precise tracking of body parts, and its enhanced correlation properties can be used to distinguish between human and nonhuman objects. Maximal Likelihood (ML) criterions to derive kinematic features and processing methods to estimate the subject activity level and activity type were derived and tailored to the wideband sonar. For tracking and association of the echoes reflected from the different body part, an efficient approximation of the sequential ML estimator was derived in the natural time-space domain, which eases the exploitation of the a priori knowledge about the human subject target. For classification of the activity, a weighted two level nested k-nearest neighbor classifier was applied on only four kinematic features. A set of experiments with five subjects, performing three different activity types of standing, walking, and swinging upper limbs, was carried out in a typical indoor environment. The proposed technology has managed to classify well the different activity types and demonstrated the potential of this technology for continuous assessment of various kinematic features of humans in indoor environment with reduced costs, under any light, smoke, or humidity conditions. This can be useful for instance for monitoring patients at home, and for detecting intruders.

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Section: A Pre-processingmentioning

confidence: 99%

“…4b represent the chosen branch metric magnitudes. The sum of branch matrices with the lowest value over the constraint length is chosen and maximizes the ML probability criterion in (10). Object A is a static object.…”

Section: ) Sequential Mle Approximationmentioning

confidence: 99%

Noncontact Wideband Sonar for Human Activity Detection and Classification

2014

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“…Other methods perform online channel estimation, frequently based on measurements between anchor nodes [19,20]. However, these are incompatible with unknown environments, or require sensors beyond communication devices [18].…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, if the application requires a coarse localisation, only, either for navigation or topology estimation purposes, the RSSI can still be useful. Several RSSI-based methods rely on a priori channel measurements [17,18]. However, those may be unavailable or unreliable due to lack of previous knowledge on the environment or severe changes that might have affected it.…”

Section: Related Workmentioning

confidence: 99%

RSSI-based relative localisation for mobile robots

Oliveira¹,

Almeida³

et al. 2014

Ad Hoc Networks

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a b s t r a c tIn this work, we develop an anchor-less relative localisation algorithm aimed to be used in multi-robot teams. The localisation is performed based on the Received Signal Strength Indicator (RSSI) readings collected from the messages exchanged between nodes. We use the RSSI as a rough estimate of the inverse of distance between any pair of communicating nodes, and we claim that such estimates provide a coarse information of the nodes relative localisation that is still suitable to support several coordination tasks. In addition, we introduce a relative velocity estimation framework based on the RSSI measurements. This framework uses consecutive distance measurements and position estimates to provide the relative velocity vectors for all the nodes in the network.To accomplish this, we propose using a Kalman filter and the Floyd-Warshall algorithm to generate smooth RSSI pairwise signal distance for all nodes. Then we use Multidimensional Scaling to obtain relative positions from the pairwise distances. Finally, due to anchor unavailability, relative positions are adjusted to reflect the continuous mobility by using geometric transformations, thus obtaining smoother trajectories for mobile nodes. This allows us to estimate velocity and to establish a correspondence between orientation in the physical world and in the relative coordinates system.Additionally, we study the impact of several parameters in calculating the network topology, namely different approaches to provide a symmetric distances matrix, the period of the matrix dissemination, the use of synchronisation of the transmissions, and the filtering of the RSSI data. Experimental results, with a set of MicaZ motes, show that the period of matrix dissemination is the most relevant of the parameters, specifically with larger periods providing the best results, however, shorter periods are shown to be possible as long as the transmissions are synchronised.

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“…It has different attenuation amplitude, in different environments. In WSN (Wireless Sensor Network), the commonly used wireless signal propagation models are: free space propagation model, 1og-distance path loss model, Hata model, log-distance distribution model, and so forth [14,15].…”

Section: Rssi Ranging Modelmentioning

confidence: 99%

Improved RSSI Positioning Algorithm for Coal Mine Underground Locomotive

Wang

Han

et al. 2015

Journal of Electrical and Computer Engineering

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Aiming at the large positioning errors of traditional coal mine underground locomotive, an improved received signal strength indication (RSSI) positioning algorithm for coal mine underground locomotive was proposed. The RSSI value fluctuates heavily due to the poor environment of coal mine underground. The nodes with larger RSSI value corrected by Gaussian-weighted model were selected as beacon nodes. In order to reduce the positioning error further, the estimated positions of the locomotives were corrected by the weighted distance correction method. The difference between actual position and estimated position of beacon node was regarded as the positioning error and was given a corresponding weight. The results of simulation show that the positioning accuracy of Gaussian-weighted model is better than statistical average model and Gaussian model and it has a high positioning accuracy after correcting positioning error correction. In the 10 m of communication range, positioning error can be maintained at 0.5 m.

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Enhanced calibration technique for RSSI-based ranging in body area networks

Cited by 30 publications

References 17 publications

Noncontact Wideband Sonar for Human Activity Detection and Classification

Noncontact Wideband Sonar for Human Activity Detection and Classification

RSSI-based relative localisation for mobile robots

Improved RSSI Positioning Algorithm for Coal Mine Underground Locomotive

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