We have implemented a TDOA multilateration of transmitters on an unmodified rtl-sdr receiver using transmitters with known location as a timing reference. We present a brief theoretical background and describe the measurement process which includes several approaches that correct the timing and frequency errors between the receivers. Additionally, we have implemented an angle of arrival direction finder using coherent rtl-sdr.

Time-Difference-of-Arrival (TDOA) location estimation is central to an OFDM based Precision Personnel Locator system being developed at WPI. Here we describe a component of the effort towards characterizing the performance of such a system and verifying the functionality of hardware and software implementations. The performance degradations due to noise in the received signal and misalignments between transmitter and receiver clock and heterodyne frequencies are investigated. This investigation involves development of a MATLAB simulator for the entire system, experimental measures using a prototype implementation and linearized analytic analysis of specific subsystems. The three types of characterizations are compared, confirming agreement, and analytic results are used to demonstrate construction of a system engineering design tool.

<p>The market for vertical takeoff and landing unmanned aerial vehicles, VTOL UAVs, is growing rapidly. To reciprocate the demand of VTOL UAVs in offshore applications, CybAero has developed a novel concept for landing on moving objects called MALLS, Mobile Automatic Launch and Landing Station. MALLS can tilt its helipad and is supposed to align to either the horizontal plane with an operator adjusted offset or to the helicopter skids. Doing so, eliminates the gyroscopic forces otherwise induced in the rotordisc as the helicopter is forced to change attitude when the skids align to the ground during landing or when standing on a jolting boat with the rotor spun up. This master’s thesis project is an attempt to get the concept of MALLS closer to a quarter scale implementation. The main focus lies on the development of the measurement methods for achieving the references needed by MALLS, the hori- zontal plane and the plane of the helicopter skids. The control of MALLS is also discussed. The measurement methods developed have been proved by tested implementations or simulations. The theories behind them contain among other things signal filtering, Kalman filtering, sensor fusion and search algorithms. The project have led to that the MALLS prototype can align its helipad to the horizontal plane and that a method for measuring the relative attitude between the helipad and the helicopter skids have been developed. Also suggestions for future improvements are presented.</p>

<p>This master thesis investigates different approaches to data compression on common types of signals in the context of localization by estimating time difference of arrival (TDOA). The thesis includes evaluation of the compression schemes using recorded data, collected as part of the thesis work. This evaluation shows that compression is possible while preserving localization accuracy.</p><p>The recorded data is backed up with more extensive simulations using a free space propagation model without attenuation. The signals investigated are flat spectrum signals, signals using phase-shift keying and single side band speech signals. Signals with low bandwidth are given precedence over high bandwidth signals, since they require more data in order to get an accurate localization estimate.</p><p>The compression methods used are transform based schemes. The transforms utilized are the Karhunen-Loéve transform and the discrete Fourier transform. Different approaches for quantization of the transform components are examined, one of them being zonal sampling.</p><p>Localization is performed in the Fourier domain by calculating the steered response power from the cross-spectral density matrix. The simulations are performed in Matlab using three recording nodes in a symmetrical geometry.</p><p>The performance of localization accuracy is compared with the Cramér-Rao bound for flat spectrum signals using the standard deviation of the localization error from the compressed signals.</p>

Indoor localization systems have a variety of applications such as tracking of assets, indoor robot navigation, and monitoring of people (e.g. patients) in hospitals or at home. Global positioning system (GPS) offers location accuracy of several meters and is mainly used for outdoor location-based applications as its accuracy degrades significantly in indoor scenarios. Wireless local area networks (WLAN) have also been used for indoor localization, but the accuracy is too low and power consumption of WLAN terminals is too high for most applications. Ultra-wideband (UWB) localization is superior in terms of accuracy and power consumption compared with GPS and WLAN localization, and is thus more suitable for most indoor location-based applications [1-4]. The accuracy and precision requirements of localization systems depend on the specific characteristics of the applications. For example, centimeter or even millimeter localization accuracy is required for dynamic part tracking, while decimeter accuracy might be sufficient for tracking patients in hospitals or at home. Note that accuracy is not the only aspect of the overall performance of the system. Factors such as cost, range, and complexity should also be considered in system design. In the first part of this dissertation, a centimeter-accurate UWB localization system is developed. The technical challenges to achieve centimeter localization accuracy are investigated. Since all the receivers are synchronized through wire connection in this system, a wireless localization system with centimeter accuracy is introduced in order to make the system easier for deployment. A two-step synchronization algorithm with picosecond accuracy is presented, and the system is tested in a laboratory environment. The second part of this dissertation focuses on reducing the complexity of UWB localization systems when the localization accuracy requirement is relaxed. An UWB three-dimensional localization scheme with a single cluster of receivers is proposed. This scheme employs the time-of-arrival (TOA) technique and requires no wireless synchronization among the receivers. A hardware and software prototype that works in the 3.1-5.1 GHz range is constructed and tested in a laboratory environment. An average position estimation error of less than 3 decimeter is achieved by the experimental system. This TOA scheme with receivers in a single unit requires synchronization between the transmitter and the receiver unit. In order to further reduce system complexity, a new time-difference-of-arrival localization scheme is proposed. This scheme requires multiple units, each operating on its own clock. It avoids synchronization between the transmitter and receivers, and thus makes the development of the transmitter extremely simple. The performance of this system is simulated and analyzed analytically, and turns out to be satisfactory for most indoor localization applications. / Graduation date: 2013

In indoor environment, the multi-sensor system can be used as an efficient solution for target location process, in terms of lower estimation cost, due to the factor that sensors have the advantages of low power, simple, cheap, and low operation complexity. However, the location methods and the placements of designed multisensor have great impact on the location performance. Based on the time difference of arrival (TDOA), the present research utilizes linear-correction spherical-interpolation (LCSI) method to estimate the location of its targets. The method is a combination of the linear-correction least-squares method and the spherical-interpolation method. Apart from the usual process of iterative, nonlinear minimization, and consequently, under the influence of noise interference and target-sensor geometry, the spherical-interpolation method will produce better results; therefore, SI method is used in place of the LS part of the LCLS method and named as the LCSI method. The objective is to correct the SI method to generate a better estimate performance. In addition to the performance issues, the limitation of the methods will also be examined. The geometric dilution of precision (GDOP) of the TDOA location method in the 3-D scenario is demonstrated with the effects on location performance of both inside and outside of the multi-sensor formation. Programmed 3-D scenario are used in the simulations, where cases with three different multiple sensor formations and two different target heights are investigated. From the simulation results of various location methods, it can be seen that LCSI has has its advantages over other methods in the wireless TDOA location.

The market for vertical takeoff and landing unmanned aerial vehicles, VTOL UAVs, is growing rapidly. To reciprocate the demand of VTOL UAVs in offshore applications, CybAero has developed a novel concept for landing on moving objects called MALLS, Mobile Automatic Launch and Landing Station. MALLS can tilt its helipad and is supposed to align to either the horizontal plane with an operator adjusted offset or to the helicopter skids. Doing so, eliminates the gyroscopic forces otherwise induced in the rotordisc as the helicopter is forced to change attitude when the skids align to the ground during landing or when standing on a jolting boat with the rotor spun up. This master’s thesis project is an attempt to get the concept of MALLS closer to a quarter scale implementation. The main focus lies on the development of the measurement methods for achieving the references needed by MALLS, the hori- zontal plane and the plane of the helicopter skids. The control of MALLS is also discussed. The measurement methods developed have been proved by tested implementations or simulations. The theories behind them contain among other things signal filtering, Kalman filtering, sensor fusion and search algorithms. The project have led to that the MALLS prototype can align its helipad to the horizontal plane and that a method for measuring the relative attitude between the helipad and the helicopter skids have been developed. Also suggestions for future improvements are presented.

Ultra Wideband (UWB) signal can offer an accurate location service in wireless sensor networks because its high range resolution. Target tracking by multiple sensors can provide better performance, but the centralized algorithms are not suitable for wireless sensor networks. In additional, the non line of sight (NLOS) propagation error leads to severe degradation of the accuracy in location systems. In this thesis, NLOS identification and mitigation technique utilizing modified biased Kalman filter (KF) is proposed to reduce the NLOS time of arrival (TOA) errors in UWB environments. We combine the modified biased Kalman filter with sliding window to identify and mitigate different degree of NLOS errors immediately. In order to deal with the influence of inaccurate NLOS angle of arrival (AOA) measurements, we also had a discussion on AOA selection and fusion methods. In the distributed location structure, we used the extended Information filter (EIF) to process the formulated time difference of arrival (TDOA) and AOA measurements for the target positioning and tracking. Instead of using extended Kalman filter, extended Information filter can assimilate selected AOA easily without dynamic dimensions. The sensors are divided into different groups for distributed TDOA/AOA location to reduce computation and then each group can assimilate information from other groups easily to maintain precise location. The simulation results show that the proposed architecture can mitigate NLOS errors effectively and improve the accuracy of target positioning and tracking from distributed location and data fusion in wireless sensor networks.

In indoor environment, the multi-sensor system has been proved to be an efficient solution for target locating process in terms of lower estimation cost. However, the placement of designed multi-sensor has great impact on the location performance in an indoor environment. Based on the time difference of arrival (TDOA), closed-form least-square location methods, including the spherical-interpolation (SI) and the spherical-intersection (SX) methods, are used in the estimation of target locations. The two methods are apart from the usual process of iterative and nonlinear minimization. Consequently, under the influence of noise interference, the performance of the two methods also produce different results. In addition to the above issues, the limitation of these methods will also be examined. The geometric dilution of precision (GDOP) effects of TDOA location on location performance of both inside and outside of the multi-sensor environment in the 2-D scenario have been studied in the past. This thesis aims to further advance the performance of GDOP in 3-D scenarios, analyze the differences, and propose the suitable needs. Programmed 3-D scenario simulations are used in this research, designed according to multiple sensor arrays and the moving latitude of a target. The Setup interprets the degree of multi-sensor separation, and distances from targets to the sensor array. A suitable location algorithm and optimal multi-sensor deployments in an indoor environment were proposed according to the simulation results.

In wireless location system, geometric relationship between the base station (BS) and the mobile station (MS) may affect the accuracy of MS location estimate. The effect is called Geometric Dilution of Precision (GDOP). Given the information of geometric configuration of BS and MS locations, the GDOP value can be calculated accordingly. In fact, the GDOP value is considered as ratio factor between the location error and measurement noise. A higher GDOP value indicates larger location error in the location estimator. Therefore the GDOP can be utilized as an index for observing the location precision of the MS under different geometric layout. The accuracy of location estimation can be improved by changing the BS device element locations. In the thesis, a time different of arrival (TDOA) wireless location system with mobile base station (MBS) is considered. Changing the geometric layout between the BS and the MS by relocating the MBS, the GDOP effect can be reduced and the accuracy of location estimation also can therefore be improved. Since the simulated annealing (SA) is capable of escaping the local minimum and finding the global minimum in an objective function, the SA algorithm is used in finding the best solution in a defined function based on the GDOP distribution. The best solution is then the destination of an MBS in the process of MS location estimation. When relocating an MBS from its initial location to the best location, it is likely that the MBS enters regions with high GDOP effects. To avoid the problem, the steepest descent (SD) algorithm is utilized for path planning. First, we establish the objective function which consists of the GDOP information and the angle of movement. A nearby location that has the minimum value of objective function is selected as the next move. The process continues until the MBS reaches the destination. A variety of cases are investigated by computer simulations. Simulation results show that the proposed approach can effectively find the best locations for MBSs to relocate. Based on the relocation and path planning, the GDOP effects can be reasonably reduced, and therefore the higher location accuracy is achieved.