449,978 research outputs found

    Compressive Time Delay Estimation Using Interpolation

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    Time delay estimation has long been an active area of research. In this work, we show that compressive sensing with interpolation may be used to achieve good estimation precision while lowering the sampling frequency. We propose an Interpolating Band-Excluded Orthogonal Matching Pursuit algorithm that uses one of two interpolation functions to estimate the time delay parameter. The numerical results show that interpolation improves estimation precision and that compressive sensing provides an elegant tradeoff that may lower the required sampling frequency while still attaining a desired estimation performance.Comment: 5 pages, 2 figures, technical report supporting 1 page submission for GlobalSIP 201

    The Burger Court—The First Ten Years

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    In this report we study estimation of time-delays in linear dynamical systems with additive noise. Estimating time-delays is a common engineering problem, e.g. in automatic control, system identification and signal processing. The purpose with this work is to test and evaluate a certain class of methods for time-delay estimation, especially with automatic control applications in mind. The class of methods consists of estimating the time-delay from the Laguerre transform of the input and output signals. The methods are evaluated experimentally with the aid of simulations and plots of approximation error, plots of original and Laguerre approximated input and output signals, plots of estimates, plots of RMS error, tables of ANOVA and plots of confidence intervals for different cases. The results are: Only certain input signals, e.g. steps, are useful. Systems with a not too fast dynamics give better estimation quality than pure time-delay systems despite the fact that the estimation methods were derived for pure time-delay systems. The Laguerre pole should be chosen in a certain way. The number of Laguerre functions should be as a high as possible

    Inter-sensor propagation delay estimation using sources of opportunity

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    Propagation delays are intensively used for Structural Health Monitoring or Sensor Network Localization. In this paper, we study the performances of acoustic propagation delay estimation between two sensors, using sources of opportunity only. Such sources are defined as being uncontrolled by the user (activation time, location, spectral content in time and space), thus preventing the direct estimation with classical active approaches, such as TDOA, RSSI and AOA. Observation models are extended from the literature to account for the spectral characteristics of the sources in this passive context and we show how time-filtered sources of opportunity impact the retrieval of the propagation delay between two sensors. A geometrical analogy is then proposed that leads to a lower bound on the variance of the propagation delay estimation that accounts for both the temporal and the spatial properties of the sources field

    Delay Estimation from noisy time series

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    We propose here a method to estimate a delay from a time series taking advantage of analysis of random walks with delay. This method is applicable to a time series coming out of a system which is or can be approximated as a linear feedback system with delay and noise. We successfully test the method with a time series generated by discrete Langevin equation with delay.Comment: Tentatively scheduled to appear as a Rapid Communication in Phys. Rev. E., March 199

    Impact of Imperfect Parameter Estimation on the Performance of Multi-User ARGOS Receivers

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    In this paper, we analyze the performance of Successive Interference Cancelation (SIC) receivers in the context of the ARGOS satellite system. Multi-user SIC receivers are studied in presence of imperfect estimates of signal parameters. We derive performance graphs that show the parameter ranges over which a successful demodulation of all users is possible. First, the graphs are derived in the context of perfect parameter estimation. Then, imperfect parameter estimation is considered. Erroneous estimations affect both the amplitude and the time delay of the received signal. Carrier frequencies are assumed to be accurately measured by the receiver. ARGOS SIC receivers are shown to be both robust to imperfect amplitude estimation and sensitive to imperfect time delay estimation

    Joint Estimation of the Time Delay and the Clock Drift and Offset Using UWB signals

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    We consider two transceivers, the first with perfect clock and the second with imperfect clock. We investigate the joint estimation of the delay between the transceivers and the offset and the drift of the imperfect clock. We propose a protocol for the synchronization of the clocks. We derive some empirical estimators for the delay, the offset and the drift, and compute the Cramer-Rao lower bounds and the joint maximum likelihood estimator of the delay and the drift. We study the impact of the protocol parameters and the time-of-arrival estimation variance on the achieved performances. We validate some theoretical results by simulation.Comment: Accepted and published in the IEEE ICC 2014 conferenc

    Iterative synchronisation and DC-offset estimation using superimposed training

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    In this paper, we propose a new iterative approach for superimposed training (ST) that improves synchronisation, DC-offset estimation and channel estimation. While synchronisation algorithms for ST have previously been proposed in [2],[4] and [5], due to interference from the data they performed sub-optimally, resulting in channel estimates with unknown delays. These delay ambiguities (also present in the equaliser) were estimated in previous papers in a non-practical manner. In this paper we avoid the need for estimation of this delay ambiguity by iteratively removing the effect of the data “noise”. The result is a BER performance superior to all other ST algorithms that have not assumed a-priori synchronisation

    Almost Linear Complexity Methods for Delay-Doppler Channel Estimation

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    A fundamental task in wireless communication is channel estimation: Compute the channel parameters a signal undergoes while traveling from a transmitter to a receiver. In the case of delay-Doppler channel, i.e., a signal undergoes only delay and Doppler shifts, a widely used method to compute delay-Doppler parameters is the pseudo-random method. It uses a pseudo-random sequence of length N; and, in case of non-trivial relative velocity between transmitter and receiver, its computational complexity is O(N^2logN) arithmetic operations. In [1] the flag method was introduced to provide a faster algorithm for delay-Doppler channel estimation. It uses specially designed flag sequences and its complexity is O(rNlogN) for channels of sparsity r. In these notes, we introduce the incidence and cross methods for channel estimation. They use triple-chirp and double-chirp sequences of length N, correspondingly. These sequences are closely related to chirp sequences widely used in radar systems. The arithmetic complexity of the incidence and cross methods is O(NlogN + r^3), and O(NlogN + r^2), respectively.Comment: 4 double column pages. arXiv admin note: substantial text overlap with arXiv:1309.372
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