A Factor-Graph-Based TOA Location Estimator

Jhi, Hwa-Lu; Chen, Jung-Chieh; Lin, Chih-Hung; Huang, Chin-Tseng

doi:10.1109/twc.2012.040412.110520

Cited by 22 publications

(19 citation statements)

References 24 publications

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“…It may be difficult to achieve the LOS condition in areas with a size of 1000 × 1000 m 2 especially in (sub)urban environments. However, instead, we can include the error due to the non-LOS components to the variance of the measurement error as shown in [20,21], where the variances are different between the sensors. For simplicity, we assume that the variance σ 2 θ of the measurement error is common to all sensors as in [6-8, 10, 11].…”

Section: Simulation Resultsmentioning

confidence: 99%

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A new DOA-based factor graph geolocation technique for detection of unknown radio wave emitter position using the first-order Taylor series approximation

Aziz

Anwar

Matsumoto

2016

J Wireless Com Network

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This paper proposes a new geolocation technique to improve the accuracy of the position estimate of a single unknown (anonymous) radio wave emitter. We consider a factor graph (FG)-based geolocation technique, where the input are the samples of direction-of-arrival (DOA) measurement results sent from the sensors. It is shown that the accuracy of the DOA-based FG geolocation algorithm can be improved by introducing approximated expressions for the mean and variance of the tangent and cotangent functions based on the first-order Taylor series (TS) at the tangent factor nodes of the FG. This paper also derives a closed-form expression of the Cramer-Rao lower bound (CRLB) for DOA-based geolocation, where the number of samples is taken into account. The proposed technique does not require high computational complexity because only mean and variance are to be exchanged between the nodes in the FG. It is shown that the position estimation accuracy with the proposed technique outperforms the conventional DOA-based least square (LS) technique and that the achieved root mean square error (RMSE) is very close to the theoretical CRLB.

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Section: Simulation Resultsmentioning

confidence: 99%

“…As shown in Fig. 2, the messages of (20) and 21, (m A θ →x , σ 2 A θ →x ) and (m B θ →y , σ 2 B θ →y ), produced by the nodes A θ and B θ , respectively, are forwarded to the estimated target position variable nodes x and y. According to the message-passing principle, now the reverse process is invoked.…”

Section: The Proposed Techniquementioning

confidence: 99%

A new DOA-based factor graph geolocation technique for detection of unknown radio wave emitter position using the first-order Taylor series approximation

Aziz

Anwar

Matsumoto

2016

J Wireless Com Network

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“…Many kinds of FG positioning techniques based on the various measurements described above have been developed. The TOA-FG [21] technique used the signal propagation time between the radio transmitter and APs to estimate the distance, but this requires the clocks of both to be synchronous. In order to be free from the limitation of clock synchronization between the radio transmitter and APs, TDOA-FG method was proposed in [22].…”

Section: Introductionmentioning

confidence: 99%

RSSD-based 3-D localization of an unknown radio transmitter using weighted least square and factor graph

Zhang

Jiang

2019

J Wireless Com Network

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Realizing accurate detection of an unknown radio transmitter (URT) has become a challenging problem due to its unknown parameter information. A method based on received signal strength difference (RSSD) fingerprint positioning technique and using factor graph (FG) for 2-D scenario has been developed. However, the URT positioning under 3-D scenario is more difficult with the large number of unknown parameters and has greater practical significance. In addition, the previous RSSD-based FG model is not accurate enough to express the relationship between the RSSD and corresponding location coordinates since the RSSD variances of reference points are different in practice. This paper proposes a more accurate 3-D FG model to reduce the influence of difference of RSSD measurement variances on positioning accuracy effectively by utilizing weighted least square (WLS). With the proposed RSSD-based 3-D WLSFG model and sum-product rule, positioning process of the proposed 3-D RSSD-WLSFG algorithm is derived. To verify the feasibility of the proposed method, we also explores the effects of different signal receiver numbers and grid distances on positioning accuracy. The simulation experiment results show that the proposed algorithm can obtain the best positioning performance compared with the conventional K nearest neighbor (KNN) algorithm and RSSD-FG algorithm under different grid distances and signal receiver numbers.

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“…Many kinds of FG positioning techniques based on the various measurements described above have been developed in recent years. The TOA-FG [13,14] technique uses the time of signal propagation between the radio transmitter and APs to estimate the distance, but it requires the clocks of both to be synchronous. In order to be free from the limitation of clock synchronization between the radio transmitter and the APs, a TDOA-FG technique utilizing hyperbolic approach is proposed in [15].…”

Section: Introductionmentioning

confidence: 99%

An RSSD-Based Fingerprint Positioning Method for Detection of an Unknown Radio Transmitter Using WLS and Factor Graph

Zhang

Jiang

2018

Mathematical Problems in Engineering

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Realizing accurate detection of an unknown radio transmitter (URT) has become a challenge problem due to its unknown parameter information. A method based on received signal strength difference (RSSD) fingerprint positioning technique and using factor graph (FG) has been successfully developed to achieve the localization of an URT. However, the RSSD-based FG model is not accurate enough to express the relationship between the RSSD and the corresponding location coordinates since the RSSD variances of reference points are different in practice. This paper proposes an enhanced RSSD-based FG algorithm using weighted least square (WLS) to effectively reduce the impact of RSSD measurement variance difference on positioning accuracy. By the use of stochastic RSSD errors between the measured value and the estimated value of the selected reference points, we utilize the error weight matrix to establish a new WLSFG model. Then, the positioning process of proposed RSSD-WLSFG algorithm is derived with the sum-product principle. In addition, the paper also explores the effects of different access point (AP) numbers and grid distances on positioning accuracy. The simulation experiment results show that the proposed algorithm can obtain the best positioning performance compared with the conventional RSSD-based K nearest neighbor (RSSD-KNN) and RSSD-FG algorithms in the case of different AP numbers and grid distances.

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A Factor-Graph-Based TOA Location Estimator

Cited by 22 publications

References 24 publications

A new DOA-based factor graph geolocation technique for detection of unknown radio wave emitter position using the first-order Taylor series approximation

A new DOA-based factor graph geolocation technique for detection of unknown radio wave emitter position using the first-order Taylor series approximation

RSSD-based 3-D localization of an unknown radio transmitter using weighted least square and factor graph

An RSSD-Based Fingerprint Positioning Method for Detection of an Unknown Radio Transmitter Using WLS and Factor Graph

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