TDOA-based Methods Research Articles

Underwater Acoustical Localization of the Black Box Utilizing Single Autonomous Underwater Vehicle Based on the Second-Order Time Difference of Arrival

Underwater acoustic localization (UWAL) is a useful technique, and is applied in finding the acoustical sources, such as the black box. The existing UWAL methods are mainly based on the time of arrival (TOA), the time difference of arrival (TDOA), and the direction of arrival (DOA), which need the time synchronization, the knowledge of signal period, and the high precision angular measurement, respectively. However, these conditions are difficult to be satisfied in the scene of locating the black box utilizing single autonomous underwater vehicle. In this article, we propose the definition of second-order time difference of arrival (STDOA) and establish the localization model based on the STDOA. The proposed STDOA-based method eliminates the unknown signal period and overcomes the restriction of the traditional TDOA-based method. Combined with the particle filter, target tracking algorithm based on the STDOA is also presented. Precision analysis and the simulation results validate the effectiveness of the STDOA-based method and prove that the proposed method achieves a comparable localization precision compared with the TOA-based method and the TDOA-based method, and a higher precision compared to the DOA-based method.

Three Passive TDOA-AOA Receivers Based Flying-UAV Positioning in Extreme Environments

In this paper, motivated by the fact that precisely positioning a flying unmanned aerial vehicle (UAV) by passive radio frequency (RF) measurements are being troubled by the extreme non-line-of-sight (NLOS) environments, we propose a 3D joint time difference of arrival (TDOA) and angle of arrival (AOA) NLOS localization method for flying UAVs using three receivers. Compared with the existing positioning schemes based on the received signal strength (RSS), TDOA, time of arrival (TOA), and AOA methods, the advantage of the proposed method is that we do not need many receivers or priori NLOS statistics, which significantly decreases the cost in practice. Simulation results demonstrate that the positioning mean square error (MSE) of the proposed method is closer to the Cramer-Rao lower bound of TDOA-based method than the existing positioning methods. Moreover, the simulation results verified the reliability of the proposed method.

Algebraic solution for three‐dimensional TDOA/AOA localisation in multiple‐input–multiple‐output passive radar

The problem of estimating the location of a single target from time difference of arrival (TDOA) and angle of arrival (AOA) measurements using multi-transmitter multi-receiver passive radar system with widely separated antennas is discussed. A closed-form two-step target position estimator is presented and analysed. Using the measured AOAs, the method is able to resolve the weakness of the TDOA-based methods in estimating the target height. Several weighted least-squares minimisations are employed by the method to produce a location estimate. A weighting matrix in each step is employed to provide a significant improvement in the performance of the algorithm. The Cramer-Rao lower bound (CRLB) for target localisation accuracy is also developed. The proposed estimator is analytically shown to reach the CRLB for Gaussian TDOA and AOA noises at moderate noise level. Simulation studies indicate that the proposed hybrid TDOA/AOA location scheme performs better than any of the other algorithms, especially in the z -direction.

Gaussian filter for TDOA based sound source localization in multimedia surveillance

Although multimedia surveillance systems are becoming increasingly ubiquitous in our living environment, automated multimedia surveillance systems based on video camera lacks the robustness and reliability most of the time in several real applications. To overcome this drawback, audio sensory devices have been taken into account in a considerable amount of research. For example, Sound Source Localization (SSL) may indicate potential security risks and could point the camera in that direction. In this paper, a reliable sound source localization based on Time-Difference-Of-Arrival (TDOA) is explored. The novel aspect of our approach includes a TDOA based Gaussian filter to improve the accuracy and stability of sound source localization. The advantage of our proposed algorithm is its extensive integration with various TDOA-based methods in all kinds of microphone array. The Experimental comparison shows significant improvement over the state of the art TDOA-based algorithm.

複数フレームのCSP係数を用いたTDOA推定による複数人物定位·追跡

In this paper, multi-speaker localization methods using voice signal are proposed. Sound source localization systems consisting of many microphones have been widely researched. In our laboratory, we have researched sound source localization of persons based on TDOA (Time Difference of Arrival) between distributed microphones for the purpose of efficient use of air conditioner and lighting in the office . Localization systems based on sound such as footsteps or voice are superior to those based on image data in terms of privacy-consciousness and utility in the dark. As sound source localization methods, beamforming, subspace methods and TDOA-based methods are widely used. CSP (Cross-power Spectrum Phase) analysis is one of the most famous method to estimate TDOA. We have researched sound source localization methods using CSP analysis because it spends less calculation cost than beamforming or subspace methods. However, CSP analysis doesn't work well by itself in the real office environment because of sound lasting for a long time, reverberations, low SNR, and so on. The main cause of difficulty in sound source localization in such a case is the “weak correlation” between different sound signals. In this paper, it is shown that the bad effect of the “weak correlation” can be improved by our proposed methods, Wiener-filter-based CSP analysis and H-CSP (Histogram-CSP) analysis. H-CSP analysis is a statistics data analysis method for CSP coefficients which uses the histogram of CSP coefficients. In this research, the effectiveness of proposed methods are shown by sound source localization experiments in the case sound sources are stable and the case sound sources are moving.

Development of Locating System of Pulsed Electromagnetic Interference Source Based on Advanced TDOA Estimation Method

A locating system based on an advanced time difference of arrival (TDOA) estimation method is developed to locate the position of a discharge source to avoid pulsed electromagnetic interference (PEMI) with the surrounding radio communication environment. In general, from the waveforms of PEMI waves received by an antenna array, the source position can be located or the direction of arrival (DOA) of the EM waves can be estimated by applying TDOA-based methods. However, owing to noises and multipath waves that occur at the metal surfaces of electric power equipment, the estimation accuracy of the TDOA may decrease, and the location accuracy will be degraded. To improve the accuracy of TDOA estimation, we propose a new TDOA estimation technique. In our developed locating system, PEMI waves are received by a four-antenna-square array and the DOA is estimated from the TDOA, which is estimated using the generalized cross-correlation phase transform method in combination with the proposed technique. A PEMI source is ultimately located by aiming a charge-coupled device camera, installed at the center of the antenna array, at the estimated DOA. The estimation accuracy of the locating system is evaluated through experimental measurements. The results show that the developed locating system can locate the position of a PEMI source existing within about 30 m from the system with high accuracy.

Practical localization system for consumer devices using zigbee networks

As the era of ubiquitous computing dawns, there is a growing need for a reliable, efficient positioning and tracking system. A localization system involves ongoing tracking of the location of assets and personnel. This paper presents a practical localization system for consumer devices on Zigbee networks. The proposed system is based on timedifference-of-arrival (TDOA). Localization based on TDOA involves estimating the location of the device by calculating the time-difference-of-arrival of the signal received from a device. In order to calculate the time difference of the signal, TDOA-based methods require precision time measurements of the signal, and reader time synchronization accurate to within a few nanoseconds. We also propose a precise time stamping unit, which enables the system to determine the arrival time of the radio signal, and a precision time synchronization protocol, which enables readers to have a reference clock. In addition, this paper includes an experimental performance evaluation of the localization system. The performance shows that the localization system has a DRMS of approximately two meters in a harsh environment.

Direction of Arrival Estimation Using the Parameterized Spatial Correlation Matrix

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> The estimation of the direction-of-arrival (DOA) of one or more acoustic sources is an area that has generated much interest in recent years, with applications like automatic video camera steering and multiparty stereophonic teleconferencing entering the market. DOA estimation algorithms are hindered by the effects of background noise and reverberation. Methods based on the time-differences-of-arrival (TDOA) are commonly used to determine the azimuth angle of arrival of an acoustic source. TDOA-based methods compute each relative delay using only two microphones, even though additional microphones are usually available. This paper deals with DOA estimation based on spatial spectral estimation, and establishes the parameterized spatial correlation matrix as the framework for this class of DOA estimators. This matrix jointly takes into account all pairs of microphones, and is at the heart of several broadband spatial spectral estimators, including steered-response power (SRP) algorithms. This paper reviews and evaluates these broadband spatial spectral estimators, comparing their performance to TDOA-based locators. In addition, an eigenanalysis of the parameterized spatial correlation matrix is performed and reveals that such analysis allows one to estimate the channel attenuation from factors such as uncalibrated microphones. This estimate generalizes the broadband minimum variance spatial spectral estimator to more general signal models. A DOA estimator based on the multichannel cross correlation coefficient (MCCC) is also proposed. The performance of all proposed algorithms is included in the evaluation. It is shown that adding extra microphones helps combat the effects of background noise and reverberation. Furthermore, the link between accurate spatial spectral estimation and corresponding DOA estimation is investigated. The application of the minimum variance and MCCC methods to the spatial spectral estimation problem leads to better resolution than that of the commonly used fixed-weighted SRP spectrum. However, this increased spatial spectral resolution does not always translate to more accurate DOA estimation. </para>

Standardization of mobile phone positioning for 3G systems

Finding the location of the mobile phone is one of the important features of the 3G mobile communication system. Many valuable location-based services can be enabled by this new feature. Telecommunication managers and engineers are often puzzled by location terminologies and techniques as well as how to implement them, since location systems are not natural evolution from past generations of telecommunication systems. In this paper, we discuss briefly why locating mobile phone becomes a hot topic and what technologies are being studied. We then describe and clarify the latest standards issues surrounding the positioning methods specified for 3G systems. These include cell-ID-based, assisted GPS, and TDOA-based methods, such as OTDOA, E-OTD, and A-FLT.