TDOA

Non Co-Operative Identification (NCI) / Automatic Target Recognition (ATR) in Air, Ground and Maritime Applications is a key issue in the compilation process of tactical situation. Classification and identification is a process having various aspects. Classification and identification techniques using acoustic or electromagnetic signatures, imaging systems or other distinguishing paramaters are employed in different systems. Some techniques about Target Motion Analysis (TMA), which can improve the classification and identification process, are presented in this paper. The classical TMA problem is estimating the target motion parameters such as position, speed, acceleration and heading of target using acoustical bearings only. Although it is commonly associated with the acoustic underwater localization problems in conjunction with submarine warfare domain, the same problem problem appears in other target tracking systems which also requires passive localization of target and estimation of target motion. Once the target motion parameters are estimated, the speed can be used to distinguish a torpedo from a submarine in an underwater acoustic environment or similarly a missile from an airborne platform in an electromagnetic environment. More importantly, the motion patterns and kinematic characteristics of the target provide valuable information for classifying a target or even identifying the target with the utilization of an intelligence database. Correct determination of target position using multisensors, as in the TMA case, is also a crucial point for identification systems, allowing to correlate the other informations from those sensors. This study is focused on TMA algorithms using time difference of arrival (TDOA) information rather than the ones using only bearing information. The TDOA methods propose a better accuracy compared to bearing only methods because time accuracy of a receiver can be better than its bearing accuracy. This study compares performances of bearing only TMA methods with TDOA based algorithms and hybrid algorithms using both TDOA and bearing data in different scenarios. Applicability of these methods is also discussed at the end.

In this paper, a new learning approach for sound source localization is presented using ad hoc either synchronous or asynchronous distributed microphone networks based on time differences of arrival (TDOA) estimation. It is first to propose a new concept in which coordinates of a sound source location are defined as functions of TDOAs, computing for each pair of microphone signals in the network. Then, given a set of pre-recorded sound measurements and their corresponding source locations, the multilevel B-Splines based learning model is proposed to be trained by the input of the known TDOAs and the output of the known coordinates of the sound source locations. For a new acoustic source, if its sound signals are recorded, the correspondingly computed TDOAs can be fed into the learned model to predict the location of the new
source. Superiorities of the proposed method are to incorporate acoustic characteristics of a targeted environment and even remaining uncertainty of TDOA estimations into the learning model before conducting its prediction and to be applicable for both synchronous or asynchronous distributed microphone sensor networks. Effectiveness of the proposed algorithm in terms of localization accuracy and computational cost in comparisons with state-of-the-art methods was extensively validated on both synthetic simulation experiments as well as in three real-life environments.

The time delay of arrival (TDOA) between multiple microphones has been used since 2006 as a source of information (localization) to complement the spectral features for speaker diarization. In this paper, we propose a new localization feature, the intensity channel contribution (ICC) based on the relative energy of the signal arriving at each channel compared to the sum of the energy of all the channels. We have demonstrated that by joining the ICC features and the TDOA features, the robustness of the localization features is improved and that the diarization error rate (DER) of the complete system (using localization and spectral features) has been reduced. By using this new localization feature, we have been able to achieve a 5.2% DER relative improvement in our development data, a 3.6% DER relative improvement in the RT07 evaluation data and a 7.9% DER relative improvement in the last year's RT09 evaluation data.

Abstract: Modern smartphones are a great platform for Location Based Services (LBS). While outdoor LBS for smartphones has proven to be very successful, indoor LBS for smartphones has not yet fully developed due to the lack of an accurate positioning technology. In this paper we present an accurate indoor positioning approach for commercial off-the-shelf (COTS) smartphones that uses the innate ability of mobile phones to produce ultrasound, combined with Time-Difference-of-Arrival (TDOA) asynchronous trilateration. We evaluate our indoor positioning approach by describing its strengths and weaknesses, and determine its absolute accuracy. This is accomplished through a range of experiments that involve variables such as position of control point microphones, position of phone within the room, direction speaker is facing and presence of user in the signal path. Test results show that our Lok8 (locate) mobile positioning system can achieve accuracies better than 10 cm in a real-world e...

Abstract: GPS is a well-established technique for location-finding, but mobile phone-based methods are generally less expensive to implement, and can give reasonable accuracies. These techniques can thus be useful to network operators in providing services based on geographical ...

Underwater source localization problems are complicated and challenging: a) the sound propagation speed is often unknown and the unpredictable ocean current might lead to the uncertainties of sensor parameters (i.e. position and velocity); b) the underwater acoustic signal travels much slower than the radio one in terrestrial environments, thus resulting into a significantly severe Doppler effect; c) energy-efficient techniques are urgently required and hence in favour of the design with a low computational complexity. Considering these issues, we propose a simple and efficient underwater source localization approach based on time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements, which copes with unknown propagation speed and sensor parameter errors. The proposed method mitigates the impact of the Doppler effect for accurately inferring the source parameters (i.e. position and velocity). The Cramér-Rao lower bounds (CRLBs) for this kind of localization are derived and, moreover, the analytical study shows that our method can yield the performance that is very close to the CRLB, particularly under small noise. The numerical results not only confirm the above conclusions but also show that our method outperforms other competing approaches. Index Terms—Underwater localization, algebraic solution, sound propagation speed uncertainty, sensor node uncertainty, time difference of arrival (TDOA), frequency difference of arrival (FDOA).

Localization of nodes in an infrastructure less network serves many purposes. Several issues relating to
security, routing, etc it can be solved if only the actual location of nodes were known. Existing approaches
estimate the location of a node in a network by using received signal strength indicator (RSSI), Time of
Arrival, Time difference of Arrival and, if directional antennas are available, Direction of Arrival. In these
methods the localization accuracy is less (in the order of 20cm). The aim of this paper is to localize nodes
in adhoc networks with improved accuracy using ultra wide band.The proposed method uses a train of low
amplitude pulses of high bandwidth, which reduces the energy consumption, effects due to small scale
fading, and dispersion in time and frequency. The network was simulated in NS-2 with UWB extension and
the localization accuracy was found to be improved (upto 1cm).

In this paper, we consider the problem of positioning, travel direction detection and speed estimation of GSM-based mobile phones. Many techniques are proposed using several technologies like GSM, UMTS or WiFi. Once these technologies are mature enough to be deployed, they will have significant impact on automotive telematics and modern public transit systems. We produce a technique for speed estimation

This paper describes an effective method for dynamic location estimation by Kalman Filter for range-based wireless network. The problem of locating a mobile terminal has received significant attention in the field of wireless communications. In this paper, Kalman Filter with TDOA technique describes the ranging measurement tracking approach. Kalman filter is used for smoothing range data and mitigating the NLOS errors. The paper presents a simple recursive model by using time difference of arrival based location measurement and incorporating state equality constraints in the Kalman filter. From the process of Kalman filtering, the standard deviation of the observed range data can be calculated and then used in NLOS/LOS hypothesis testing. The proposed recursive locating algorithm, compared with a Kalman tracking algorithm that estimates the target track directly from the TDOA measurements, will be comparatively more robust to measurement errors because it updates the technique that ...