Tesi sul tema "TDOA"

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.

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.

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.

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.

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.

Vid Positionsbestämning av radiosändare med TDOA(Time Difference Of Arrival) är det traditionella sättet att låta varje uppmätt tidsskillnad definiera en hyperbelgren på vilken sändaren befinner sig. Skärningspunkten mellan två eller fler hyperbelgrenar ger sändarens position.

Målet med examensarbetet är att identifiera möjliga sändarpositioner och detektera mångtydigheter. Problemet har lösts med kägelsnittsmetoden som låter tre mottagares positioner och deras uppmätta tidsskillnader definiera ett kägelsnitt där sändarens position är i en av dess fokuspunkter.

Ultra wideband (UWB) communication systems refers to systems whose bandwidth is many times greater than the “narrowband” systems (refers to a signal which occupies only small amount of space on the radio spectrum). UWB can be used for indoor, communications for high data rates, or very low data rates for substantial link distances because of the extremely large bandwidth, immune to multi-path fading, penetrations through concrete block or obstacles. UWB can also used for short distance ranging whose applications include asset location in a warehouse, position location for wireless sensor networks, and collision avoidance.

In order to verify analytical and simulation results with real-world measurements, the need for experimental UWB systems arises. The Institute of Communications Engineering [IANT] has developed a low-cost experimental UWB positioning system to test UWB based positioning concepts. The mobile devices use the avalanche effect of transistors for simple generation of bi-phase pulses and are TDMA multi-user capable. The receiver is implemented in software and employs coherent cross-correlation with peak detection to localize the mobile unit via Time-Difference-Of-Arrival (TDOA) algorithms. Since the power of a proposed UWB system’s signal spread over a very wide bandwidth, the frequencies allocated to multiple existing narrowband systems may interfere with UWB spectrum. The goal of the filters discussed in this project is to cancel or suppress the interference while not distort the desired signal. To investigate the interference, we develop a algorithm to calculate the interference tones. In this thesis, we assume the interference to be narrowband interference (NBI) modeled as sinusoidal tones with unknown amplitude, frequency and phase. If we known the interference tones then it may be removed using a simple notched filter. Herein, we chose an adaptive filter so that it can adjust the interference tone automatically and cancel. In this thesis I tested adaptive filter technique to cancel interference cancellation (ie) LMS algorithm and Adaptive Noise Cancellation (ANC) technique. In this thesis performance of the both filters are compared.

The use of spread spectrum signals has increased dramatically in military applications. Finding methods for detecting and positioning of these signals have become interesting research areas for signal intelligence purposes. One method is to measure the time difference of arrival (TDOA) that occurs when two receivers are synchronous and spatially separated. Based on the TDOA-technique an audio-demonstrator has been developed and implemented. This report describes the theory for how sound received in microphones can be used to extract information about the transmitter’s position from the measured time difference. The technique has been implemented and tested in a non-silencing room where sound from a loudspeaker has been recorded into MATLAB through the use of microphones. By correlating the received signals, an estimation of the time difference can be made. A hyperbolic function represents all possible transmitter positions for the given time difference. With three of more receivers a single position can be estimated. With an accuracy within a couple of hundreds of a degree, a direction can be estimated with simulated signals for a given SNR (usually 25dB) or a position within a few centimetres when the transmitter is a couple of meters away. Tests with real audio signals show less satisfying results. The position can at best be estimated with an accuracy of 5% of the distance to the receiver when the microphones are spread out 0.7m apart. The performance of the audio-demonstrator can be improved by using better methods for finding the points of intersection between hyperbolas and by weighting the estimated time differences.

Source localization using TDOA measurements has been an important research topic mainly because of its wide applications in practical localization systems. The TDOA localization accuracy is known to be very sensitive to the sensor position errors and even a small amount of sensor position errors can cause significant performance loss. This thesis considers the use of calibration emitters to improve the source location estimate from TDOAs when the sensor positions are subject to random errors. The principle behind is that with calibration emitters, extra TDOA measurements that contain information on the true sensor positions can be obtained and if properly exploited, they are able to mitigate the effect of sensor position errors and improve the source localization accuracy. This thesis investigates, in four different localization scenarios (scenarios (i)- (iv)), the effect of calibration TDOA measurements on the source localization accuracy and how to efficiently explore them in the localization algorithm design to achieve the optimum performance.

We consider in scenario (i) the TDOA localization of a source in the presence of sensor position errors when a calibration emitter at perfectly known position is available. The CRLB of the source location estimate for this case is derived and it indicates that the utilization of calibration TDOAs can lead to great improvement in localization accuracy over the case without a calibration emitter. The performance of the differential calibration (DC) method used in GPS to mitigate the effect of satellite position uncertainty and other errors using a calibration emitter is analyzed theoretically. It is shown that in general, the DC method cannot attain the CRLB accuracy. We then develop a novel algorithm that explores the TDOA measurements from both the calibration emitter and the unknown source to estimate the source location. The newly proposed solution is in closed-form and more importantly, we prove analytically that unlike the DC method, it can reach the CRLB accuracy under two mild conditions.

Scenario (ii) is practically more realistic than scenario (i) in the sense that besides the known sensor positions, the calibration positions also have random errors and the number of calibration emitters can be greater than one. We establish the CRLB of the source location estimate for this case and quantify the performance degradation due to the calibration position errors. The sensitivity of the source location estimate to the calibration position errors is investigated and the result indicates that the source localization accuracy can be severely degraded if the calibration position errors are simply ignored. Based on this observation, a closed-form TDOA localization algorithm that takes both the calibration position errors and the sensor position errors into account is developed. The proposed solution explores all the calibration TDOAs to improve performance and it is shown analytically to reach the CRLB accuracy under mild conditions.

In scenario (iii), multiple sources at unknown locations need to be localized from TDOA measurements when the sensor positions are not known accurately. This problem includes the scenario where a single source is located with calibration emitters at completely unknown positions as a special case. The multiple sources are assumed to be disjoint and for each source, a separate set of TDOA measurements is obtained. Recognizing that in literatures, only iterative methods are available for the multiple source localization problem, we propose a closed-form solution that does not require iterations and is computationally more attractive. The new concept of hypothesized source positions is introduced in the algorithm development. Through theoretical performance analysis, we show that the proposed solution is able to attain the CRLB localization accuracy under small noise conditions. The developed algorithm can also provide improved sensor positions as a byproduct. (Abstract shortened by ProQuest.)

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.