D-SLATS: Distributed Simultaneous Localization and Time Synchronization

Through the last decade, we have witnessed a surge of Internet of Things (IoT) devices, and with that a greater need to choreograph their actions across both time and space. Although these two problems, namely time synchronization and localization, share many aspects in common, they are traditionally treated separately or combined on centralized approaches that results in an ineffcient use of resources, or in solutions that are not scalable in terms of the number of IoT devices. Therefore, we propose D-SLATS, a framework comprised of three different and independent algorithms to jointly solve time synchronization and localization problems in a distributed fashion. The First two algorithms are based mainly on the distributed Extended Kalman Filter (EKF) whereas the third one uses optimization techniques. No fusion center is required, and the devices only communicate with their neighbors. The proposed methods are evaluated on custom Ultra-Wideband communication Testbed and a quadrotor, representing a network of both static and mobile nodes. Our algorithms achieve up to three microseconds time synchronization accuracy and 30 cm localization error

Multi-Tag Access for a High Precision Ultra-Wideband Localization System

Ultra-Wideband (UWB) wireless positioning systems have many advantages for track- ing and locating items in indoor environments. Surgical navigation and industrial process control are potential applications for high accuracy UWB localization systems with millimeter or sub-millimeter accuracy. I present improvements made to an existing high accuracy, multi-tag, UWB localization system. The goal of this thesis was to improve the multi-tag performance of this system while maintaining the high localization accuracy, and to utilize the UWB system for digital communications allowing the existing narrowband 2.4 GHz transceiver to be eliminated. This thesis presents a proof-of-concept for a multi-tag, UWB localization system utilizing orthogonal time hopping multiple access (OTHMA). Asynchronous transmit- only UWB digital communication allows identification of tags without the use of a narrowband control channel, and time di↵erence of arrival (TDOA) accomplishes localization. A digital sampling circuit is used for both localization and digital communication. I address the inherent challenge of collisions in an asynchronous transmit-only system while maintaining high accuracy and high update rates. An experimental system was developed consisting of two base stations and two tags allowing measurement of 1-D localization accuracy along with system update rates. The experimental results for localization accuracy were equivalent to results from the existing system while update rates were improved by greater than 50%

Grid-based Hybrid 3DMA GNSS and Terrestrial Positioning

The paper discusses the increasing use of hybridized sensor information for GNSS-based localization and navigation, including the use of 3D map-aided GNSS positioning and terrestrial systems based on different geometric measurement principles. However, both GNSS and terrestrial systems are subject to negative impacts from the propagation environment, which can violate the assumptions of conventionally applied parametric state estimators. Furthermore, dynamic parametric state estimation does not account for multi-modalities within the state space leading to an information loss within the prediction step. In addition, the synchronization of non-deterministic multi-rate measurement systems needs to be accounted. In order to address these challenges, the paper proposes the use of a non-parametric filtering method, specifically a 3DMA multi-epoch Grid Filter, for the tight integration of GNSS and terrestrial signals. Specifically, the fusion of GNSS, Ultra-wide Band (UWB) and vehicle motion data is introduced based on a discrete state representation. Algorithmic challenges, including the use of different measurement models and time synchronization, are addressed. In order to evaluate the proposed method, real-world tests were conducted on an urban automotive testbed in both static and dynamic scenarios. We empirically show that we achieve sub-meter accuracy in the static scenario by averaging a positioning error of $0.64$ m, whereas in the dynamic scenario the average positioning error amounts to $1.62$ m. The paper provides a proof-of-concept of the introduced method and shows the feasibility of the inclusion of terrestrial signals in a 3DMA positioning framework in order to further enhance localization in GNSS-degraded environments

A Framework for Low Complexity Least-Squares Localization With High Accuracy

In this paper, a new framework is proposed for least-squares localization based on estimated ranges, coveringtime-difference-of-arrival (TDoA), time-of-arrival (ToA), and received signal strength (RSS) cases. The multidimensional nonlinear localization problem is first transformed to a lower dimension and then solved iteratively. Within the proposed transformed least-squares (TLS) framework, we introduce a method in which the localization problem is transformed to one dimension (1-D). In this way, compared to the classical nonlinear least-squares (NLS) type of methods, the amount of computations in each iteration is greatly reduced; a reduction of 67% for a 3-D positioning system is shown. Hence, the introduced 1-D iterative (1DI) method is fairly light on the computational load.The way to choose the 1-D parameter is proposed, and theoretical expressions for the convergence rate and the root- mean-squared error (RMSE) of the 1DI estimator are derived. Validation is performed mainly based on actual ultra-wideband (UWB) radio measurements, collected in typical office environments, with signal bandwidths varying from 0.5 to 7.5 GHz. Supplementary simulations are also included for validation. Results show that, in terms of RMSE, the 1DI method performs better than the linear least-squares (LLS) method, where the solution is obtained noniteratively, and performs similarly as NLS, especially in TDoA cases

Robust Indoor Localization in a Reverberant Environment Using Microphone Pairs and Asynchronous Acoustic Beacons

In this paper, a robust indoor localization method using microphone pairs and asynchronous acoustic beacons was proposed. The proposed method is applicable even with a two-channel microphone pair, which is the minimal configuration of a microphone array. The proposed method estimates location by using the cross-correlation functions of the measured signals as location likelihoods. Three experiments were conducted to evaluate the proposed method. Four beacons were located at the corners of a localizing area of 4 m by 4 m and emitted signals with a bandwidth of 2 kHz. The localization results were compared to the previous method with deterministic direction-of-arrival estimation. The 90th percentiles of the localization error were 0.23 m for the proposed method with two microphones, 0.19 m for the proposed method with four microphones, and 0.30 m for the previous method under conditions without significant reverberation. Under a condition with reflective walls, the 90th percentile of the localization error of the previous method increased to 0.49 m, while that of the proposed method was only increased to 0.23 m for two microphones and 0.19 m for four microphones. The proposed method contributes to a robust localization in indoor environments and relieves the constraints of receiver configuration