In time difference of arrival-based signal source location estimation, geometrical errors are caused by the location of multiple unmanned aerial vehicles (UAV). Herein, we propose a divide-and-conquer algorithm to determine the optimal location for each UAV. Simulations results confirm that multiple UAVs shifted to an optimal position and the location accuracy improved.

Source localization in a wireless sensor network (WSN) is sensitive to the sensors' positions. In practice, due to mobility, the receivers' positions may be known inaccurately, leading to non-negligible degradation in source localization estimation performance. The goal of this paper is to develop a semidefinite programming (SDP) method using time-difference-of arrival (TDOA) and frequency-difference-of-arrival (FDOA) by taking the sensor position uncertainties into account. Specifically, we transform the commonly used maximum likelihood estimator (MLE) problem into a convex optimization problem to obtain an initial estimation. To reduce the coupling between position and velocity estimator, we also propose an iterative method to obtain the velocity and position, by using weighted least squares (WLS) method and SDP method, respectively. Simulations show that the method can approach the Cramér-Rao lower bound (CRLB) under both mild and high noise levels.

This paper mainly discusses the time-difference-of-arrival (TDOA) estimation problem of digital modulation signal under impulsive noise and cochannel interference environment. Since the conventional TDOA estimation algorithms based on the second-order cyclic statistics degenerate severely in impulsive noise and the TDOA estimation algorithms based on correntropy are out of work in cochannel interference, a novel signal-selective algorithm based on the generalized cyclic correntropy is proposed, which can suppress both impulsive noise and cochannel interference. Theoretical derivation and simulation results demonstrate the effectiveness and robustness of the proposed algorithm.

3GPP (3rd Generation Partnership Project) has started to discuss D2D (Device-to-Device)-aided OTDOA (Observed Time Difference Of Arrival) as one of the mobile positioning enhancement techniques for LTE (Long Term Evolution) systems. It is a kind of multi-node based OTDOA which directly receives D2D signals from adjacent multiple UEs (User Equipment) to measure RSTD (Reference Signal's Time Difference). D2D signals provide valuable advantages in terms of OTDOA positioning because it can guarantee more reference nodes and high SNR (Signal-to-Noise Ratio) of PRS (Positioning Reference Signal). Two typical methods for multi-node based OTDOA can be applied to D2D-aided OTDOA. Multiple OTDOA positioning is one of the multi-node based methods that averages multiple results from OTDOA; however, it cannot always guarantee high accuracy due to the non-uniform geometry of UEs. OTDOA positioning based on TSE (Taylor Series Expansion) algorithm may be one of the solutions; however, it has the initial value problem and high computational complexity due to its iterative procedure. Therefore, in this paper, we propose a novel D2D-aided OTDOA positioning method which utilizes UEs not as reference node of OTDOA but as assisting node for RSTD error reduction. The proposed method can reduce RSTD error of eNB based hyperbola by using multiple hyperbola bands. The hyperbola band indicates the possible range in which a hyperbola can occur due to RSTD error. Then, by using principal axes of hyperbolas, we estimate a modified hyperbola from the overlap area of hyperbola bands, which has less RSTD error. We verify that the proposed method can effectively reduce RSTD error and improve positioning performance with lower computational complexity.

This paper proposes a moving source localization method that combines TDOA, FDOA and doppler rate measurements. First, the observation equations are linearized by introducing nuisance variables and an initial solution of all the variables is acquired using the weighted least squares method. Then, the Taylor expression and gradient method is applied to eliminate the correlation between the elements in the initial solution and obtain the final estimation of the source position and velocity. The proposed method achieves CRLB derived using TDOA, FDOA and doppler rate and is much more accurate than the conventional TDOA/FDOA based method. In addition, it can avoid the rank-deficiency problem and is more robust than the conventional method. Simulations are conducted to examine the algorithm's performance and compare it with conventional TDOA/FDOA based method.

In the localization systems based on time difference of arrival (TDOA), multipath fading and the interference source will deteriorate the localization performance. In response to this situation, TDOA estimation based on blind beamforming is proposed in the frequency domain. An additional constraint condition is designed for blind beamforming based on maximum power collecting (MPC). The relationship between the weight coefficients of the beamformer and TDOA is revealed. According to this relationship, TDOA is estimated by discrete Fourier transform (DFT). The efficiency of the proposed estimator is demonstrated by simulation results.

An instrumental variable (IV) based linear estimator is proposed for effective target localization in sensor network by using time-difference-of-arrival (TDOA) measurement. Although some linear estimation approaches have been proposed in much literature, the target localization based on TDOA measurement still has a room for improvement. Therefore, we analyze the estimation errors of existing localization estimators such as the well-known quadratic correction least squares (QCLS) and the robust least squares (RoLS), and demonstrate advantages of the proposition by comparing the estimation errors mathematically and showing localization results through simulation. In addition, a recursive form of the proposition is derived to consider a real time application.

In this paper, time-difference estimation of filtered random signals passed through multipath channels is discussed. First, we reformulate the approach based on innovation-rate sampling (IRS) to fit our random signal model, then use the IRS results to drive the nonlinear least-squares (NLS) minimization algorithm. This hybrid approach (referred to as the IRS-NLS method) provides consistent estimates even for cases with sub-Nyquist sampling assuming the use of compactly-supported sampling kernels that satisfies the recently-developed nonaliasing condition in the frequency domain. Numerical simulations show that the proposed NLS-IRS method can improve performance over the straight-forward IRS method, and provides approximately the same performance as the NLS method with reduced sampling rate, even for closely-spaced time delays. This enables, given a fixed observation time, significant reduction in the required number of samples, while maintaining the same level of estimation performance.

In OFDMA-based digital duplexing (DD) systems, the effective channel impulse response (CIR) is lengthened due to time difference of arrivals (TDoAs) from adjacent subscriber stations (SSs). In this letter, a time-domain shortening filter (TSF) is proposed to shorten the effective CIR by maximizing signal-to-interference ratio for pulse shortening (SIRPS). A time-domain window (TW) is also proposed to reduce the effect of inter-carrier interference (ICI) due to CFO in OFDMA-based DD systems, by maximizing the signal-to-interference and noise ratio for window (SINRW).

To overcome the shortcomings of conventional cellular positioning, a novel cooperative location algorithm that uses the available peer-to-peer communication between the mobile terminals (MTs) is proposed. The main idea behind the proposed approach is to incorporate the long- and short-range location information to improve the estimation of the MT's coordinates. Since short-range communications among MTs are characterized by high line-of-sight (LOS) probability, an improved spring-model-based cooperative location method can be exploited to provide low-cost improvement for cellular-based location in the non-line-of-sight (NLOS) environments.

In 3GPP (3-rd Generation Partnership Project) LTE (Long Term Evolution) system, the use of PRS (Positioning Reference Signal) for OTDOA (Observed Time Difference of Arrival) based positioning method has been agreed. However, PRSs can be overlapped at the receiver side in synchronous network because the frequency shift pattern of PRS is decided by cell ID (Identity). Moreover, in asynchronous network, the loss of orthogonality between received PRSs generates continuous interferences. Even though autonomous muting can be applied to solve the interference problems in synchronous and asynchronous networks, the muting scheme degrades the overall positioning efficiency and requires additional network complexity. Therefore, in this paper, we propose novel OTDOA based positioning methods at the receiver side to improve positioning efficiency: cancellation method of serving PRS for synchronous network, TDORS (Time Domain Orthogonal Reference Signal) generation and useful CIR (Channel Impulse Response) selection methods for asynchronous network. We verified that the proposed methods can achieve an accurate estimation and stable operation without PRS muting.

We propose an improved TDoA (Time Difference of Arrival) localization scheme based on PSO (Particle Swarm Optimization) in UWB (Ultra Wide Band) systems. The proposed scheme is composed of two steps: the re-estimation of TDoA parameters and the re-localization of tag position. In both steps, the PSO algorithm is employed to improve the performance. In the first step, the proposed scheme re-estimates the TDoA parameters obtained by traditional TDoA localization to reduce the TDoA estimation error. In the second step, the proposed scheme with the TDoA parameters estimated in the first step, re-localizes the tag to minimize the location error. Simulation results show that the proposed scheme achieves better location performance than the traditional TDoA localization in various channel environments.

An original asynchronous Ultra Wideband -- Impulse Radio (UWB-IR) wireless location system for sensor network is developed and evaluated through experiments. The system enables wireless nodes to be located and communicated with simultaneously at low power and low cost. The proposed system does not need system synchronization. Each access point of the proposed location system measures the time difference between two signals' received timing: one is from target node, and the other is from an access point, the position of which is already known. Then the position of the target nodes is calculated by a pseudo Time Difference of Arrival (TDOA) method. We first introduce the system configuration and asynchronous TDOA method adopted in this system. Next, we estimate the received-signal-timing measurement accuracy of UWB-IR signal and evaluate it in experiments using prototype UWB-IR transceivers. Then we estimate the location accuracy by the horizontal dilution of precision (HDOP) metric and show the field trial results of using the prototype UWB-IR location system.

Ultra-Wideband is an attractive technology for short range positioning, especially indoors. However, for normal 3D Time Difference of Arrival (TDOA) positioning, at least four receivers with an unblocked direct path to the transmitter are required. A requirement that is not always met. In this work, a novel method for TDOA positioning using only three receivers is presented. TDOA positioning with three receivers is possible by exploiting the knowledge of some of the indoor features, namely positions of big flat reflective surfaces, for example ceiling and walls. The proposed method was verified using data from a measurement campaign.

In real environments, the presence of ambient noise and room reverberations seriously degrades the accuracy in sound source localization. In addition, conventional sound source localization methods cannot localize multiple sound sources accurately in real noisy environments. This paper proposes a new method of multiple sound source localization using a distributed microphone system that is a recording system with multiple microphones dispersed to a wide area. The proposed method localizes a sound source by finding the position that maximizes the accumulated correlation coefficient between multiple channel pairs. After the estimation of the first sound source, a typical pattern of the accumulated correlation for a single sound source is subtracted from the observed distribution of the accumulated correlation. Subsequently, the second sound source is searched again. To evaluate the effectiveness of the proposed method, experiments of two sound source localization were carried out in an office room. The result shows that sound source localization accuracy is about 99.7%. The proposed method could realize the multiple sound source localization robustly and stably.

The conventional TDoA (Time Difference of Arrival)-based and RSS (Received Signal Strength)-based location schemes create large positioning errors because of the various wireless channel effects such as path loss, shadowing, and NLoS (Non-Line-of-Sight) components of the multipath channels. In this paper, we propose an improved wireless location scheme which performs a weighted combination of the TDoA and RSS location schemes to improve a detection probability in the mobile-WiMAX femto-cell environments.

We propose a simple asynchronous UWB (Ultra Wide Band) position location algorithm with low complexity, power consumption and processing delay. In the proposed algorithm, only a single RTTX (Round-Trip Transmission) of UWB pulses is utilized based on the ToA (Time of Arrival) principle. Hence, the proposed algorithm decreases power consumption and processing delay as compared to the basic ToA based on triple RTTXs. Moreover, unlike the TDoA (Time Difference of Arrival) algorithm, the proposed algorithm can perform the position location with low complexity since it does not require strict synchronization between multiple beacons. Simulation results using IEEE 802.15.4a UWB channel models reveal that the proposed algorithm achieves closely comparable position location performance of the basic ToA and TDoA algorithms.