TDOA Estimation Research Articles

ToA and TDoA Estimation Using Artificial Neural Networks for High-Accuracy Ranging

ToA and TDoA Estimation Using Artificial Neural Networks for High-Accuracy Ranging

Multi-objective time-frequency difference parameter sorting technology based on adaptive multi-mode particle filter

Modern new system radar has high-speed and flexible beam scheduling capability, and the widely used high repetition rate design of signals leads to a large number of uneven TDOA ambiguity points in passive TDOA estimation, which is difficult to locate accurately. The ambiguity of TDOA is caused by the pulse pairing error of HPRF radar signal in TDOA estimation. A large amount of position information is still retained in the ambiguity, and simple removal of false locating points may lead to the breakage and loss of target track. According to the PRF group variation characteristics of PRF packet radar signals, this paper proposes a multi-target time–frequency difference parameter sorting technology based on adaptive multi-mode particle filter. The technology unifies the time difference ambiguity and multi-objective problem under the Bayesian reasoning framework, adopts multi-modal particle filter method, and uses a posteriori probability recursive estimation to achieve time difference ambiguity resolution and parameter sorting. Through multi-dimensional probability association, we can realize the association, rebirth and extinction of goals. The simulation verifies the feasibility of the proposed method, which can still maintain a high accuracy of ambiguity resolution and target sorting under the condition that five targets exist at the same time and the TDOA curve intersects.

A fast TDOA and VDOA estimation method of the wideband frequency hopping signal

In the mobile multi-station passive positioning scenario, the carrier frequency hopping of the wideband frequency hopping communication signal will produce a changing Doppler frequency shift. Therefore, it is not possible to directly estimate the Doppler frequency difference of the observed signal containing multiple pulses. In this case, only the time difference and frequency difference of the single-hop signal can be estimated, but the accuracy is low. The existing methods often need the carrier frequency of each FH pulse signal as a priori information, and the high computational complexity of the two-dimensional search method of the time difference and frequency difference is difficult to overcome. Aiming at the above problems, a fast and high-precision estimation algorithm for the time difference of arrival and velocity difference of wideband frequency hopping signals is proposed in this paper. Firstly, the wideband frequency hopping signal is segmented in the time domain with multiple pulses as the unit, the signal model of time-varying time difference is established, and the time difference of each short-time segment is estimated by the generalized cross-correlation algorithm. The estimated values of the initial time difference and Doppler velocity difference can be worked out by least squares fitting of the time difference sequence obtained from the single pulse estimation. Finally, taking the Link16 data link signal as an example, the simulation experiment of the proposed method is conducted, which verifies the correctness and performance superiority of the algorithm.

A Mobile Phone Uplink CPDP-DTDOA Positioning Method Using UAVs for Search and Rescue

This article proposes a mobile phone passive positioning system using unmanned aerial vehicles (UAVs) to detect the uplink signals based on orthogonal frequency-division multiplexing (OFDM) for search and rescue. Reducing the influence of time synchronization error on time of arrival (TOA) estimation, the system sets up a reference node to broadcast reference signals at the subframe of uplink signals. The differential time difference of arrival (DTDOA) estimation method is adopted to achieve high-precision positioning. At the same time, an efficient TOA estimation method for DTDOA called cross power delay profile (CPDP) estimation is proposed, which can reduce the computational effort of TOA estimation by up to 50% compared to conventional DTDOA. The performance and Crámer–Rao lower bound of CPDP-DTDOA estimation are compared with conventional DTDOA estimation and TDOA estimation. The effects of signal-to-noise ratio (SNR) and sampling rate on the performance of CPDP-DTDOA are evaluated. The experiment and simulation demonstrate that CPDP-DTDOA can achieve time synchronization and obtain unbiased TOA estimation even at low sampling rates when the reference signal is under line-of-sight (LOS) and high SNR, satisfying the low-power design for UAV platforms.

Accuracy of Positioning of Ground Sources Using Geostationary Repeaters

Introduction. Currently, there is a significant increase in the number of relay satellites in geostationary orbit. However, frequent incidents of illegal use of the satellites frequency resource, as well as unintentional and deliberate interference with other users are fixed. In this regard, it becomes necessary to evaluate accuracy and applicability of various methods for determining the location of sources of illegal and interfering radio emission with different signal parameters and with different levels of uncertainty for relay satellite coordinates and velocities.Aim. To study and to evaluate the accuracy of methods of geolocation of radio emission sources operating through geostationary relay satellites, with different signal parameters and with different levels of uncertainty for relay satellite coordinates and velocities.Materials and methods. Imitation modeling and the theory of digital signal processing were used.Results. Factors influencing the accuracy of the estimation of TDOA and FDOA parameters when determining the position of radio emission sources, which operate via relay satellites located in geostationary orbit, were considered. As a result of simulation, the estimate of the accuracy of the considered geolocation methods was obtained. It depends on the bandwidth of radio emission source signal, on the recording duration and on the level of a priori uncertainty relatively the relay satellites coordinates and velocities. Recommendations for the application of the considered methods in various conditions were formulated.Conclusions. Conclusions and recommendations formulated as a result of the study, will allow one to choose the most appropriate geolocation method to improve the accuracy of radio emission sources locating depending on conditions and signal parameters.

Estimation of arrival time difference of partial discharge ultrasonic signals based on nonlinear transformation and covariant

Ultrasonic signals will be generated when high voltage equipment is partially discharged. In order to de-termine the location of partial discharge, the time difference between ultrasonic signal and sensor can be used. In this paper, Alpha stable distribution is used to model noisy ultrasonic signals collected during actual partial discharge, and a nonlinear transformation-covariant time difference estimation method is proposed. Firstly, the signal-to-noise ratio can be improved to a certain extent by preprocessing the noisy signal based on the arctangent nonlinear transformation. Then, the covariant correlation function is used to measure the similarity of the two signals arriving at the sensor, and according to the position of the peak value of the covariant correlation function, the time difference information of signal arrival is obtained. On the basis of theoretical analysis, the experimental results of computer simulation are discussed and summarized. Com-pared with generalized correlation method and covariant algorithm, the proposed method is more suitable for TDOA estimation of PD ultrasonic signals in low SNR and impulsive noise environment.

An Acoustic-Based Surveillance System for Amateur Drones Detection and Localization

Due to cost reduction and device miniaturization, amateur drones are now widely used in numerous civilian and commercial applications. However, the abuse of amateur drones has resulted in emerging threats to personal privacy and public security. To alleviate these threats, we design an acoustic-based surveillance system, which can achieve the capacity of amateur drones detection and localization with 24/7 (24 hours per day and 7 days per week under normal circumstances) availability. In the designed system, a detection fusion algorithm and a TDOA estimation algorithm based on the Bayesian filter are applied to improve the performance of drone detection and localization. Field experiments are carried out, and the results demonstrate that the designed system can detect and locate an amateur drone in real time with high accuracy and 24/7 availability.

CRLB for joint estimation of TDOA, phase, FDOA, and Doppler rate

To avoid decline of FDOA estimation precision caused by relative Doppler companding, Doppler rate has to be considered and estimated jointly with TDOA, phase, and FDOA. However, CRLB of the joint estimation is still unclear. This study addresses on derivation of the CRLB. First, the joint estimation model is constructed. Then, the signal-specific CRLB for any type of signal and a simplified CRLB for stationary and constant-envelope signal are derived, respectively. Finally, as a verification, the derived bound is compared with previous bounds for the special cases of TDOA, phase, and FDOA estimation, which shows that authors’ bound is reasonable. In addition to the conventional scenarios of TDOA, phase and FDOA estimation, their bound can also indicate the error characteristic of Doppler rate, which can be used to evaluate estimation performance and forecast location accuracy using Doppler rate.

TDOA Estimation Algorithm Based on Generalized Cyclic Correntropy in Impulsive Noise and Cochannel Interference

TDOA Estimation Algorithm Based on Generalized Cyclic Correntropy in Impulsive Noise and Cochannel Interference

High Resolution Estimation of AoA, AoD and TdoA from MIMO Channel Sounding Measurements with Virtual Antenna Arrays: Maximum-Likelihood vs. Unitary Tensor-ESPRIT

Estimating the parameters of a geometric propagation model from MIMO channel sounding measurements will be considered, which requires the solution of an inverse problem. Thus, a model of the measured data is derived, which incorporates a model of the measurement system as well as the parameters of interest. Based on the data model a maximum-likelihood estimator will be derived to infer the model parameters. Because virtual antenna arrays are considerer, formed by step-wise rotating directive antennas at transmitter and receiver side, the MIMO measurements are conducted in the beam-space. Hence, the data model can be described by a multidimensional convolution of the measurement system and the propagation channel. Based on the convolutional modelling, the parameter estimation problem is transformed into a harmonic retrieval problem, which can be solved by an Unitary Tensor-ESPRIT algorithm. The maximum-likelihood and ESPRIT estimator are compared by Monte-Carlo simulations according to their root-mean-square estimation error.

Analisis Perkiraan TDOA menggunakan Algoritma LMS Adaptif pada Pelacakan Paus Lodan

AbstrakPenelitian mengenai perkiraan TDOA dalam pelacakan paus lodan telah dilakukan[1] yang menggunakan Teager-Kaiser operator dalam peningkatan akurasi perkiraan nilai TDOA untuk pelacakan paus lodan menggunakan algoritma LMS adaptif. Namun demikian, belum dilakukan penelitian lebih lanjut mengenai faktor konvergensi (μ) yang tepat (cepat dan akurat) pada perkiraan TDOA menggunakan algoritma LMS adaptif untuk pelacakan paus lodan. Akan dilakukan analisis perkiraan nilai TDOA menggunakan algoritma LMS adaptif pada pelacakan posisi paus lodan dengan variasi nilai μ. Pada penelitian ini, sebagai acuan untuk menentukan nilai μ yang tepat, digunakan hasil pelacakan paus pada penelitian [2].Perkiraan TDOA menggunakan algoritma LMS Adaptif pertama kali dipublikasikan oleh Benesty [3]. Pendekatan yang dilakukan berdasarkan pada perkiraan tanggap impulsional dari sumber ke penerima. Pada algoritma LMS adaptif dilakukan pembaruan nilai koefisien dengan μ sebagai langkah adaptasi. Nilai TDOA diperoleh dari selisih jarak dua tanggap impulsional.Dari hasil penelitian diperoleh hasil bahwa perubahan nilai μ mempengaruhi kecepatan perkiraan TDOA menggunakan algoritma LMS adaptif. Akan tetapi, nilai μ yang tidak tepat mengakibatkan hasil pelacakan paus tidak akurat. Dari penelitian ini diperoleh nilai μ terbaik untuk perkiraan TDOA menggunakan algoritma LMS adaptif pada pelacakan posisi paus lodan adalah 0.01. Kata kunci— perkiraan TDOA, LMS adaptif, faktor konvergensi, pelacakan paus lodan AbstractResearch on TDOA estimation in sperm whale tracking has been done [1] that uses the Teager - Kaiser operator in improving accuracy the TDOA estimation using adaptive LMS algorithm on sperm whale tracking. However, further researches on the right convergence factor (μ) (fast and accurate) in TDOA estimation using adaptive LMS algorithms for sperm whale tracking have not been performed. Will be analyzed the TDOA estimation using adaptive LMS algorithm in sperm whale tracking with the variation of μ. As a reference to determine the right value of μ, the results of sperm whale tracking[2] is used.TDOA estimation using Adaptive LMS algorithm was first published by Benesty [3]. The approach taken is based on estimation of the impulse responses from source to receivers. In the adaptive LMS algorithm function updates the coefficient with μ as adaptation step. TDOA values obtained from the difference between the two impulse responses.From the results, values changing of μ affect the speed of TDOA estimation using the LMS adaptive algorithm. However, the wrong value of μ is lead to inaccurate sperm whale tracking results. The best value of μ for TDOA estimation using the LMS adaptive algorithm for sperm whale tracking is 0.01. Keywords— TDOA estimation, adaptive LMS, convergence factor, sperm whale tracking

分布式协同无源定位中的数据压缩技术

分布式协同无源定位技术中，到达时差定位技术(Time Differences of Arrive, TDOA)具有定位精度高、定位速度快、抗干扰能力强的优点。但是，TDOA定位需要不同位置的传感器节点将采样值传送到同一个节点进行时差估计，需要大量的数据传输。为了避免大规模的数据传输，数据压缩技术被应用到定位之中。为了达到较高的压缩比，对信号波形进行矢量量化(Vector Quantization, VQ)。仿真不同维数、不同码书大小对TDOA估计精度的影响。实验证明矢量量化能够取得巨大的压缩比，且不失TDOA估计精度，有效的解决TDOA定位技术的大规模数据传输问题。 In data compression technology of distributed cooperative passive location, TDOA has the advan-tages of high positioning accuracy, positioning speed and strong anti-interference ability. But, TDOA location needs different sensors to transmit the received signal to the same sensor to make TDOA estimation, which needs massive data transmission. In order to solve the massive data transmission, data compression is used in location. For getting higher compression ratio, vector quantization is used to deal with the signal. Through simulating the different vector dimension and different codebook size to find what affect the TDOA estimation accuracy. Experiments prove that vector quantization can obtain high compression ratio without loss of the accuracy of TDOA estimation, and solve the problem of massive data transmission in TDOA effectively.

Achieving Network Localizability in Nonlocalizable WSN with Moving Passive Event

Localization is an essential service in most of the wireless sensor network (WSN) applications. This paper focuses on utilizing the moving passive event to achieve the network localizability in an initially nonlocalizable network. The hybrid TDOA and distance measurement is firstly used in the network localizability. We propose the sufficient conditions in terms of node localizability and network localizability, respectively. Besides, a more promising TDOA estimation approach, which is approximately synchronization-free, is proposed to well support our localization approach. We design a corresponding algorithm in distributed manner for the implementation of our approach. Compared with the current works, our approach requires no extra hardware cost and any adjustment of the current topology of the network and hence is more feasible in practice. We evaluate the performance of our approach via extensive simulations on a one-thousand-node network. Simulation results show that our TDOA estimation approach achieves the accuracy of 0.1 milliseconds. More than 90% nodes can be localized within 0.04 r, where r denotes the ranging radius of a sensor.

Blind source extraction for robust speech recognition in multisource noisy environments

This paper proposes and describes a complete system for Blind Source Extraction (BSE). The goal is to extract a target signal source in order to recognize spoken commands uttered in reverberant and noisy environments, and acquired by a microphone array. The architecture of the BSE system is based on multiple stages: (a) TDOA estimation, (b) mixing system identification for the target source, (c) on-line semi-blind source separation and (d) source extraction. All the stages are effectively combined, allowing the estimation of the target signal with limited distortion.While a generalization of the BSE framework is described, here the proposed system is evaluated on the data provided for the CHiME Pascal 2011 competition, i.e. binaural recordings made in a real-world domestic environment. The CHiME mixtures are processed with the BSE and the recovered target signal is fed to a recognizer, which uses noise robust features based on Gammatone Frequency Cepstral Coefficients. Moreover, acoustic model adaptation is applied to further reduce the mismatch between training and testing data and improve the overall performance. A detailed comparison between different models and algorithmic settings is reported, showing that the approach is promising and the resulting system gives a significant reduction of the error rate.

Generalized State Coherence Transform for Multidimensional TDOA Estimation of Multiple Sources

According to the physical meaning of the frequency-domain blind source separation (FD-BSS), each mixing matrix estimated by independent component analysis (ICA) contains information on the physical acoustic propagation related to each source and then can be used for localization purposes. In this paper, we analyze the Generalized State Coherence Transform (GSCT) which is a non-linear transform of the space represented by the whole demixing matrices. The transform enables an accurate estimation of the propagation time-delay of multiple sources in multiple dimensions. Furthermore, it is shown that with appropriate nonlinearities and a statistical model for the reverberation, GSCT can be considered an approximated kernel density estimator of the acoustic propagation time-delay. Experimental results confirm the good properties of the transform and its effectiveness in addressing multiple source TDOA detection (e.g., 2-D TDOA estimation of several sources with only three microphones).

Data Compression Based on DFT for Passive Location in Sensor Networks

TDOA based passive location is an important application in sensor networks. The signal data must be transferred from one sensor to another, which is used to estimate TDOA. Therefore, a data compression method has to be used for the sake of reducing the volume of data. In order to improve coding efficiency, a block-encoding method based on windowed Discrete Fourier Transform (DFT) is proposed. We design a polyphase structure to achieve windowed DFT, which can achieve real time processing of the high sampling rate. Compared with transform coding to the whole data, the block-encoding method is easy to implement in engineering with lower computation complexity, and therefore saves computational resources. Simulation results show that TDOA estimation accuracy based on data block-encoding data is close to that based on the whole encoding method for high SNR.

시각동기 스위칭 GPS 중계기를 이용한 실내측위 시스템

A new method for the GPS repeater based indoor positioning is proposed and its feasibility is verified by experiments in previous paper. But the problems how can identify switching GPS repeater's ID and when switching will be occurred are remained. To solve the problem faced with, we propose the time synchronized switching GPS repeater and the methods of the detection of switching time and the estimation of TDOA. First, switching GPS repeater retransmits the signals synchronized on GPS time, sequentially. Always, first switching time is synchronized with 1 PPS. Second, we formulate the detection of switching time and the estimation of TDOA and propose the various methods. No method is existed absolutely superior to others in any conditions but the method is existed superior to others in specific condition. Finally, feasibility of indoor positioning using time-synchronized switching GPS repeater is evaluated through experiments in anechoic chamber and general environment with multipath.

Adaptive TDOA estimation in presence of impulsive noise

A fractional lower-order, moment-based adaptive algorithm for estimating the time difference of arrival between signals received at two spatially separated sensors in the presence of impulsive noise modelled as a stable process is proposed. The method is computationally efficient and is a generalisation of the simplified explicit time delay estimator. Convergence of the algorithm is analysed and simulation results are included to evaluate its estimation performance for both static and nonstationary delays.

Modified cyclic methods for signal selective TDOA estimation

A modification that applies to some recently proposed cyclostationarity-based methods for TDOA estimation is introduced. It relaxes an assumption on the noise and interference environment that characterizes all cyclostationarity-based methods so far proposed. It is shown that the modified techniques can assure satisfactory performances in noise and interference environments where the unmodified methods fail.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Comparison of autocorrelation and cross-correlation methods for signal-selective TDOA estimation

Two algorithms for signal-selective time-difference-of-arrival estimation are compared in terms of their implementation and their mean-squared errors (MSEs). A tradeoff between ease of implementation and MSE performance is shown to exist. It is shown that MSE is independent of the distance between sensors for both algorithms. >