TDOA Algorithm Research Articles

Wireless positioning method for transmission pipe gallery inspection robot based on the TDOA algorithm

A wireless sensor network for positioning an inspection robot is developed for a transmission pipe gallery environment. The time difference of the arrival algorithm optimized by the least squares method is utilized to realize the wireless positioning function of the robot in the inspection process. The developed system adopts a spiral configuration to install the sensor nodes at equal intervals on the sidewall of the transmission pipe gallery, and only 10 sensor nodes closest to the wireless signal transmission source are activated for each measurement, which avoids the poor long-distance measurement effect of the sensor, ensures sufficient accuracy, and reduces calculation costs. A wireless positioning simulation test was conducted in an experimental transmission corridor environment. The error of the simulation results is equivalent to the measurement error of a single sensor, and the error is not accumulated in the calculation of the algorithm, indicating that the algorithm has achieved good results.

EXPERIMENTAL ANALYSIS OF ACOUSTIC EMISSION PROPAGATION VELOCITIES AND ENERGY ATTENUATION LAW OF P AND S WAVES IN WOOD USING IMPROVED TDOA MEASUREMENTS

To explore the propagation law of AE signal in wood, the propagation velocity of P-wave and S-wave and the energy attenuation law of different frequency components were studied By PLB (pencil-lead break) tests. Firstly, an improvedtime-difference-of-arrival (TDOA)method was designed to determine the arrive time. Thepropagation velocities of P-wave and S-wave were calculated. Then, the Young's modulus was estimated by P-wave velocity. Finally, on thebasis of eliminating the influence of standing wave, the energy attenuation models were obtained by numerical fitting and wavelet decomposition. The results showed that the improved TDOA algorithm can calculate the propagation velocity of P-wave and S-wave at the same time through one test, and the P-wave velocity can be used to estimate the Young's modulus. P-wave propagated faster in soft wood, while S-wave propagated faster in hard wood. The higher thefrequency of AE signal, the faster the energy attenuation.

3D sensor network location spatial positioning technology based on machine learning

Abstract The purpose of this paper is to combine machine learning to locate the 3D sensor network space. Real life is mostly a three-dimensional environment. Whether it is a factory in manufacturing or a vegetation base in agriculture, it needs to be monitored and positioned. In this paper, the localization algorithm is discussed to a certain extent. This paper firstly introduces the relevant background and organizes related work. It also wrote related algorithms, such as ranging-based positioning algorithms in the free space of wireless sensors. It shows the positioning link by introducing the wireless sensor network structure system and node structure. And this paper summarizes the Bounding-box Method positioning principle, TDOA algorithm principle, and TDOA positioning principle. It then describes the gradient boosting tree classification algorithm based on machine learning, and focuses on the admiral boosting tree classification algorithm related to the experiment. This paper also describes the ranging technology combining RSSI algorithm and DV-Hop algorithm in three-dimensional space, and mentions two algorithms of RSSI and DV-Hop. In the fourth part, the machine learning coordinate prediction accuracy improvement experiment and the three-dimensional space positioning algorithm optimization experiment and result analysis are carried out. It is proved by experiments that the model evaluation effect of the gradient boosting tree classification algorithm in machine learning is the best. It can be applied to the calculation of relative position coordinates of label nodes. It then carried out the three-dimensional positioning effect test experiment of IDV-Hop algorithm. This shows that when the network density in the experimental environment reaches more than 12, the localization coverage of IDV-Hop algorithm and DV-Hop algorithm are both higher than 91%. Finally, the hybrid algorithm of RSSI and DV-Hop algorithm is used to compare the positioning accuracy, positioning coverage and bad node rate with these two algorithms. It draws the stability of the hybrid algorithm and its effects, and finally discusses and summarizes the experiments.

A Real-Time UWB Location and Tracking System Based on TWR-TDOA Estimation and a Simplified MPGA Layout Optimization

This article designs and implements a 3D moving target positioning and tracking system by using ultrawideband (UWB) technology. The result of the two-way ranging by the time difference of arrival (TWR-TDOA) positioning algorithm is adopted to result in a new resolution that is to resolve the hyperbolic equations. The proposed algorithm is applied to outdoor and indoor scenarios. To minimize the effect of the sensor layout, this article proposes a simplified multi-population genetic algorithm (MPGA) to obtain the optimum distribution of anchors, which can rapidly reduce the number of search iterations. To resolve the low stability of the TDOA algorithm in outdoor and indoor scenarios, the Kalman filter algorithm is utilized to improve the stability and positioning accuracy of this system and a good simulation effect is achieved. The test results show that the system’s positioning error is far less than that of using other methods. The whole system has a feature of high precision, high stability, low complexity, and low cost.

Design and Implementation of Real-Time Localization System (Rtls) Based on Uwb and Tdoa Algorithm

Nowadays, accurate localization plays an essential role in many fields, like target tracking and path planning. The challenges of indoor localization include inadequate localization accuracy, unreasonable anchor deployment in complex scenarios, lack of stability, and high cost. So the universal positioning technologies cannot meet the real application requirements scarcely. To overcome these shortcomings, a comprehensive Ultra Wide-Band (UWB) based RTLS is presented in this paper. We first introduce the architecture of the real-time localization system, then propose a new wireless clock synchronization (WCS) scheme, finally discuss the time difference of arrival (TDoA) algorithm. We define the time-base selection strategy for the TDoA algorithm, and analyze the relationship between anchor deployment and positioning accuracy. The Extended Kalman Filter (EKF) method is presented for non-linear dynamic localization estimation, and it performs well in terms of stability and accuracy in moving targets.

Two-Stage Channel Adaptive Algorithm for Unmanned Aerial Vehicles Localization with Cellular Networks

Unmanned aerial vehicle (UAV) is regarded as a powerful tool to expand the existing ground wireless network into aerial space. Since high mobility is an essential characteristic for UAV, it is important to carry out an accurate, real-time, and high-precision localization in terms of safe operation and communication link maintenance. The cellular network-based localization technology has provided UAV a solution with both high coverage and seamless connection. However, the complex channel environment between the UAV and terrestrial base station (BS) would have weakened the localization performance. To solve this problem, a two-stage channel adaptive algorithm for cellular-connected UAV has been proposed. The first stage of the algorithm is to revise the observation error introduced by the complex channel environment using the model of DDPG. The second stage is to locate the UAV position with TDOA algorithm using the revised observation values. Simulation results have demonstrated that the proposed algorithm can achieve the channel adaptive effect by revising the observation errors and improve location performance greatly, especially for UAVs at a relative lower altitude.

A Joint Positioning Algorithm of TDOA and TOF Based on Ultra-wideband

Ultra-wideband (UWB) positioning is a mainstream positioning technology in recent years, and the main positioning algorithms used in UWB based positioning systems are TDOA and TOA. Aiming at the problem of unstable positioning accuracy of TDOA algorithm in traditional UWB positioning system, this paper proposes a joint positioning algorithm of TDOA and TOF based on UWB. The algorithm needs only one time of TOF ranging and combined with the TDOA algorithm, the distances between all base stations and a single tag in the positioning area can be obtained. Compared with the single TDOA algorithm, the algorithm has stable measurement accuracy and can achieve the same positioning accuracy whether the tag is inside or outside the triangle formed by the base station. The simulation results show that the average positioning error of the joint positioning algorithm of TDOA and TOF is less than 10 cm. The algorithm is effective and reliable, and meets the positioning requirements.

Indoor Position System Based on Improved TDOA Algorithm

An indoor position system based on UWB modules is introduced in this paper. The time difference is obtained by the communication between the target node and the source node, and the time difference is sent to the upper computer to calculate the position of the target node with the improved TDOA algorithm and kalman filtering algorithm. The test shows that the system has the advantage of high precision and high stability.

Weighted moving average-based differential UWB indoor localisation system for high external disturbance environment

Time-based ultra-wideband (UWB) indoor localisation system is affected by clock offset, electromagnetic interference, NLOS and other external conditions, the localisation accuracy and stability will be greatly reduced. Differential GPS (DGPS) technology introduces a reference station, which transmits a pseudo range correction value to a GPS receiver for error correction, thereby largely reducing the localisation error to improve GPS localisation accuracy and localisation stability. In this paper a differential UWB localisation algorithm combined with weighted moving average is proposed by drawing on the experiences of differential GPS, focusing on clock offsets and propagation effects. At the same time, the differential UWB indoor localisation system based on TDOA algorithm is tested by Hainan EVK 2.0 experiments. The experiment results show that Differential UWB indoor localisation system can effectively improve the localisation precision and localisation stability, especially in the case of external disturbances, the overall localisation error is reduced by 23%.

Improved TDOA algorithm for underground positioning considering anchor position error

Improved TDOA algorithm for underground positioning considering anchor position error

Research on TDOA/AOA Fusion Algorithm Based on UWB Technology

This paper presents a joint UWB positioning technology and improved TDOA / AOA fusion positioning algorithm which is improved by a two-dimensional algorithm. In the framework of UWB technology, the initial coordinates of the target node are calculated by combining the measurement algorithm AOA and the TDOA algorithm in the two-dimensional plane. An improved algorithm is proposed to calculate the weight coefficient using the initial node coordinates and eliminate the error interference, and then calculate the final location of the label according to the weighting coefficient. Experimental results show that the improved TDOA / AOA fusion algorithm is significantly superior to the original TDOA / AOA fusion algorithm in positioning accuracy.

Improved Dynamic RSSI-TDOA Weighted Fusion Indoor Localization Algorithm

Due to physical factors like unstable AP signal strength and complex indoor environment, there are problems in conventional difference of time arrival (TDOA) algorithm such as inaccurate positioning, large impact on positioning accuracy caused by abnormal data. After analyzing TDOA algorithm and RSSI algorithm, this paper proposed RSSI-TDOA weighted fusion indoor localization algorithm. In order to obtain a more accurate estimate of the position, this algorithm combines improved dynamic RSSI algorithm with TDOA algorithm through two layers of data fusion. The MATLAB simulation result shows that, by using data fusion, compared to the conventional TDOA algorithm, this algorithm has a higher accuracy. Compared to conventional RSSI algorithm, it eliminates measurement errors caused by RSSI singular values.

A Novel WSNs Localization Algorithm Based on Artificial Fish Swarm Algorithm

In node localization algorithm in Wireless Sensor Networks (WSNs), the least square method is affected by the measurement error, which leads to position error of the unknown node. In order to solve the problem that the error is too high, we propose a novel WSNs localization algorithm based on artificial fish swarm (AFSA). In the proposed algorithm, artificial fish swarm, which has some advantages such as requirements for the initial value and parameter setting is not high, the optimization speed is quick and so on, is introduced in position process. Firstly, the distances between nodes are obtained by using the TDOA algorithm. Then the geometrical position of the unknown nodes is estimated by the artificial fish swarm optimization algorithm. The simulation results show that compared with the least square method, the algorithm proposed in the paper can reduce the computation amount, get the optimal solution quickly and improve the accuracy of the node without increasing the cost and power consumption. Moreover, the number of beacon nodes is relatively small, so the network cost is reduced to a certain extent.

Research on Network Scalability Based on UWB Indoor Localization System

Network Scalability is an important step in the development of UWB indoor localization system. Owing to its fine resolution and robustness in cluttered environments, UWB signals are well suited for localization purposes as they allow high ranging accuracy. TDOA algorithm based on UWB indoor localization system can achieve high-precision positioning but it requires each anchor clock synchronization. This paper mainly studied the optional of master anchor based on TDOA algorithm. It becomes an effective way to adapt to the complex communication environment. Then realized the network scalability in multiple anchor conditions and finally evaluated the performance of master anchor optional algorithm on a realistic indoor scenario. A localization error analysis on UWB indoor positioning system was performed. The smallest TDOA measurement error is 15.127 cm and the worst error is 27.230 cm, as was shown by the test results.

Collaborative Positioning in Ad Hoc Networks Using Passive Time- Differences of Arrival

Accuracy and scalability contribute to the quality of location solutions in wireless networks. While accuracy is a parameter addressed in all location technologies, scalability is often relegated. However, scalability becomes an actual issue in positioning solutions based message exchange (e.g. measuring ranges from beacons). The passive TDOA algorithm is a solution designed to localize terminals in a mobile ad hoc network in a passive way. It is achieved by computing time-differences of arrival from messages being exchanged by other network nodes (i.e. the active nodes), but just listening to the radio channel. In advanced stages of the passive TDOA algorithm (i.e. autonomous passive TDOA recently patented), it is able to compute the position of the unknown node (i.e. the passive node) and of the nodes which the listened location messages belong to (i.e. the active nodes). Thus, the requirement of active nodes informing about its own position to passive nodes is overcome. From the network perspective, the impact of this joint-position computation: it boosts the scalability since less information is transmitted and it helps to improve the accuracy of the active nodes, because passive nodes can report several positions regarding a single active node. However, the accuracy of the positions computed by means of the passive TDOA algorithm needs to be good enough to attend the user’s demands. The aim of this work is analyzing the accuracy achieved by the passive TDOA, focusing on the loss of precision due to passivity if compared with conventional two-way time-of-arrival active solutions, which passive TDOA is rely on.

RSSI를 이용한 향상된 TDOA와 Pattern Matching 간의 선택적 실내 측위에 관한 연구

This paper researches location estimating method in CDMA system. Previously proposed positioning algorithms are difficult to estimate accurate position in indoor environments, and possible to limited position. This paper proposes enhanced algorithm using received PN pilot signals from base stations to enhance previous algorithms. For estimating position, we set the threshold value and use over the threshold value in received signals. After selecting signals, we estimate position using TDOA algorithm. And the cases which TDOA algorithm cannot use to estimate position, we use Pattern Matching algorithm. The proposed method system showed the improved performance in estimating parameters and locating positions by computer simulations.

Indoor Localization System Based on an Ultrasonic Sensor Network

This paper proposes an ultrasonic localization system, which adopts ultrasonic sensors to set up a network and realizes the information interactively with control center via 485 Bus. Using TDOA algorithm realizes the localization in indoor environment, and proposes a method to gain node information, on the basis, we can get a higher degree of response speed and accuracy of the system. Take an experiment by constructing an indoor localization test terrace, to prove feasibility of the theoretical.

Acoustic Source Localization via Advanced TDoA for Self-Organization Wireless Sensor Networks

Wireless Sensor Networks (WSNs) enable susceptible sensing of the environment, offering unprecedented opportunities for observing the physical world. Acoustic source localization is an interesting topic with many possible application areas, such as intruder detection, sniper localization, automatic tracking of speakers and so on. Many existing algorithms are on the premise that the exact coordinates of sensor nodes are already known. In this paper, we propose a vector-based advanced TDoA algorithm that would calibrate the coordinate of the acoustic source by the non-prepositioned nodes. In the meanwhile, the portable sensor nodes would adjust themselves through the feedback of the estimated positions as well. Finally, we show that the proposed mechanism has high accuracy through experiments.