Backtracking-based dynamic programming for resolving transmit ambiguities in WSN localization

Schlupkothen, Stephan; Prasse, Bastian; Ascheid, Gerd

doi:10.1186/s13634-018-0536-x

“…Some of the challenges in mobility that needs to rectify involves coverage, connectivity and energy consumption. One of the most important issues over the mobile WSNs is the precise localization of mobile devices [16][17][18][19][20]. Another issue related to this localization is the coverage problem and is of three categories named barrier coverage, target coverage and area coverage.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Mobility Target Tracking with Metaheuristic Aided Target Movement Prediction Scheme in Wireless Sensor Network

Ramadevi,

Subramanyam,

Bindu

2024

Wireless Pers Commun

0

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Mobile Target Tracking is one of the most important applications in Wireless Sensor Networks (WSNs), particularly for surveillance purposes. The tracking accuracy is highly dependent on distance estimation or localization, and so far more works has been done in this aspect. This paper proposes a new energy-saving target tracking scheme with two phases: (i) Mobility Target Tracking and (ii) Target Movement Prediction. At first, the target tracking is attained by Extended Kalman Filter. Following this, the target movement is predicted with the aid of input factors such as Angle of Arrival (AoA) and Received Signal Strength (RSS), thereby the mobile node's optimal movement is predicted. This scenario is considered as the optimization crisis as the prediction of optimal node movement is one of most significant problems in WSN. In order to make the optimal prediction more precise, a new hybrid algorithm named Lion Mutated-Crow Search Algorithm (LM-CS) is introduced. The proposed algorithm combines the concept of Lion Algorithm (LA) and Cuckoo Search algorithm (CS), respectively. To the end, the performance of proposed work is evaluated over other models with respect to convergence analysis, error analysis and so on.

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“…In this process, many reference nodes are deployed in advance and a signal propagation environment will affect RSSI value. In [15], the authors developed a localization algorithm based on RSSI fingerprints. They drew the relationship between RSSI values and location in the indoor positioning region.…”

Section: Introductionmentioning

confidence: 99%

A Novel Localization Algorithm Based on RSSI and Multilateration for Indoor Environments

Du

¹

,

Yuan

²

,

Yue

³

et al. 2022

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Indoor localization algorithms based on the received signal strength indicator (RSSI) in wireless sensor networks (WSNs) have higher localization accuracy than other range-free methods. This paper considers indoor localization based on multilateration and averaged received signal strength indicator (RSSI). We propose an approach called weighted three minimum distances method (WTM) to deal with the poor accuracy of distances deduced from RSSI. Using a practical localization system, an experimental channel model is deduced to assess the performance of the proposed localization algorithm in realistic conditions. Both simulated data and measured data are used to verify the proposed method. Compared with nonlinear least squares (NLS), Levenberg–Marquardt algorithm (LM) and semidefinite programming method (SDP), simulations show that the proposed method exhibits better localization accuracy but consumes more calculation time.

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“…Some of the challenges in mobility that needs to rectify involves coverage, connectivity and energy consumption. One of the most important issues over the mobile WSNs is the precise localization of mobile devices [16][17][18][19][20]. Another issue related to this localization is the coverage problem and is of three categories named barrier coverage, target coverage and area coverage.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Mobility Target Tracking with Metaheuristic Aided Target Movement Prediction Scheme in Wireless Sensor Network

Narasapuram

¹

,

Subramanyam

²

,

Bindu

³

2022

Preprint

1

0

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Mobile Target Tracking is one of the most important applications in Wireless Sensor Networks (WSNs), particularly for surveillance purposes. The tracking accuracy is highly dependent on distance estimation or localization, and so far more works has been done in this aspect. This paper proposes a new energy-saving target tracking scheme with two phases: (i) Mobility Target Tracking and (ii) Target Movement Prediction. At first, the target tracking is attained by Extended Kalman Filter. Following this, the target movement is predicted with the aid of input factors such as Angle of Arrival (AoA) and Received Signal Strength (RSS), thereby the mobile node's optimal movement is predicted. This scenario is considered as the optimization crisis as the prediction of optimal node movement is one of most significant problems in WSN. In order to make the optimal prediction more precise, a new hybrid algorithm named Lion Mutated-Crow Search Algorithm (LM-CS) is introduced. The proposed algorithm combines the concept of Lion Algorithm (LA) and Cuckoo Search algorithm (CS), respectively. To the end, the performance of proposed work is evaluated over other models with respect to convergence analysis, error analysis and so on.

show abstract

Backtracking-based dynamic programming for resolving transmit ambiguities in WSN localization

Cited by 4 publications

References 25 publications

Adaptive Mobility Target Tracking with Metaheuristic Aided Target Movement Prediction Scheme in Wireless Sensor Network

Adaptive Mobility Target Tracking with Metaheuristic Aided Target Movement Prediction Scheme in Wireless Sensor Network

A Novel Localization Algorithm Based on RSSI and Multilateration for Indoor Environments

Adaptive Mobility Target Tracking with Metaheuristic Aided Target Movement Prediction Scheme in Wireless Sensor Network

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