Distributed time-difference-of-arrival (TDOA)-based localization of a moving target

Ennasr, Osama; Xing, Guoliang; Tan, Xiaobo

doi:10.1109/cdc.2016.7798662

Cited by 26 publications

(32 citation statements)

References 11 publications

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“…One application of the above distributed estimation scenario is in target tracking based on timedifference-of-arrival (TDOA) via a group of UAVs [25]. In this framework a group of UAVs estimate the location of a mobile target based on the time-difference-of-arrival of some beacon signal received by the UAVs.…”

Section: B Distributed Estimationmentioning

confidence: 99%

“…Further, in control literature, consensus finds applications in distributed optimization [18], flight formation [19]- [22], and multi-agent rendezvous [23], [24]. Of particular interest in aerospace system applications, along with rendezvous in 3D space, are distributed target tracking [25] and formation control via a group of UAVs. For example, in distance-based formation control the consensus protocol is used to stabilize the UAVs to form a specific geometric shape (see Section V-D for more information).…”

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confidence: 99%

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Single-Bit Consensus With Finite-Time Convergence: Theory and Applications

Doostmohammadian

2020

IEEE Trans. Aerosp. Electron. Syst.

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In this brief paper, a new consensus protocol based on the sign of innovations is proposed. Based on this protocol each agent only requires single-bit of information about its relative state to its neighboring agents. This is significant in real-time applications, since it requires less computation and/or communication load on agents. Using Lyapunov stability theorem the convergence is proved for networks having a spanning tree. Further, the convergence is shown to be in finite-time, which is significant as compared to most asymptotic protocols in the literature. Time-variant network topologies are also considered in this paper, and final consensus value is derived for undirected networks. Applications of the proposed consensus protocol in (i) 2D/3D rendezvous task, (ii) distributed estimation, (iii) distributed optimization, and (iv) formation control are considered and significance of applying this protocol is discussed. Numerical simulations are provided to compare the protocol with the existing protocols in the literature.

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Section: B Distributed Estimationmentioning

confidence: 99%

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confidence: 99%

Single-Bit Consensus With Finite-Time Convergence: Theory and Applications

Doostmohammadian

2020

IEEE Trans. Aerosp. Electron. Syst.

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“…Because the location of the positioning object is unknown, this distance is estimated from other information, such as the RSS or signal propagation time. Well-known related range-based technologies include that using received signal strength indicator (RSSI) [8,9,10,11,12], time of arrival (ToA) [13], and time difference of arrival (TDoA) [14]. The second category is that of range-free methods that do not attempt to estimate the physical distance between an anchor point and positioning object.…”

Section: Related Workmentioning

confidence: 99%

“…The time synchronization problem of ToA is solved by TDoA [14,15]. Let D 1 and D 2 denote the measured distances from the target to anchor points 1 and 2, respectively.…”

Section: Related Workmentioning

confidence: 99%

“…Owing to the location of the target is unknown, the real Euclidean distance between the target and reference point cannot be measured. Therefore, some methods have been proposed to obtain the estimated distance by inferring it from the received signal strength (RSS) [8,9,10,11,12], or signal propagation time [13,14,15]. Then, three reference points that are not collinear are selected.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Positioning System Based on Coverage Area Pruning in Wireless Sensor Networks

Huang

2018

Sensors

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Wireless sensor networks are commonly applied in environmental monitoring applications. The crucial factor in such applications is to accurately retrieve the location of a monitoring event. Although many technologies have been proposed for target positioning, the devices used in such methods require better computational abilities or special hardware that is unsuitable for sensor networks with limited ability. Therefore, a range-free positioning algorithm, named coverage area pruning positioning system (CAPPS), is proposed in this study. First, the proposed CAPPS approach determines the area that includes the target approximately by using sensor nodes that can detect the target. Next, CAPPS uses sensor nodes that cannot detect the target to prune the area to improve positioning accuracy. The radio coverage variation is evaluated in a practical scenario, and a heuristic mechanism is proposed to reduce false positioning probability. Simulation results show that the size of the positioning area computed by CAPPS is smaller than that computed using distance vector hop, angle of arrival, and received signal strength indicator by approximately 98%, 97%, and 93%, respectively. In the radio variation scenario, the probability of determining an area excluding the target can be reduced from 50%–95% to 10%–30% by applying the proposed centroid point mechanism.

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