Highly efficient techniques for mitigating the effects of multipath propagation in DS-CDMA delay estimation

Lohan, Elena Simona; Hamila, Ridha; Lakhzouri, Abdelmonaem; Renfors, Markku

doi:10.1109/twc.2004.840231

Cited by 53 publications

(45 citation statements)

References 34 publications

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“…To accommodate the problem of degraded estimation performance discussed in the previous section, an advanced ML-based algorithm, namely the multipath estimation delay lock loop (MEDLL), was proposed (Van Nee 1992, 1997Van Nee et al 1994;Townsend et al 1995;Lohan et al 2005) wherein instead of estimating all of the multipath components at once, major ones are estimated in turns. In the original MEDLL algorithm (Van Nee 1992), the parameters of the ith multipath signal are estimated aŝ…”

Section: Multipath Estimation Delay Lock Loopmentioning

confidence: 99%

“…Some of the most promising ML-based multipath estimation algorithms are first theoretically and empirically compared, and a novel technique is then proposed. The algorithms studied include basic vector ML estimation of the channel that provides a delay profile for the entire search region, multipath delay estimation lock loop (MEDLL; Van Nee 1992;Van Nee et al 1994;Townsend et al 1995;Van Nee 1997;Lohan et al 2005) that provides delay and amplitude estimates for a few of the strongest multipath components iteratively, and sequential maximum likelihood (SML; Sahmoudi and Amin 2009) that sequentially estimates the path parameters using scalar ML estimation. The disadvantages of each approach are addressed, and a novel technique is proposed that targets these disadvantages.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An advanced GNSS code multipath detection and estimation algorithm

et al. 2015

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A novel maximum likelihood-based range estimation algorithm is designed to provide robustness to multipath, which is recognized as a dominant error source in DS-CDMA-based navigation systems. The detection-estimation problem is jointly solved to sequentially estimate the parameters of each individual multipath component and predict the existence of a next possible component. A comparison between contemporary maximum likelihoodbased multipath estimation techniques and this new technique is provided. A selection of realistic channel simulation models is used to assess relative performance under different operating situations. A set of real GPS L1/CA data processing results are also presented to further assess the applicability of the proposed algorithm for urban navigation.

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Section: Multipath Estimation Delay Lock Loopmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An advanced GNSS code multipath detection and estimation algorithm

et al. 2015

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“…Among all the competitive peaks, TK selects the delay associated to that competitive peak which has the closest delay difference from the previous delay estimate. TK-based technique is chosen in the context of the paper since it has been proved that it can give very good results in the delay-estimation process when used with CDMA type of signals, as presented in [27,39]. Most recently, TK has been studied also in closed-loop model for SinBOC(1,1), modulated two paths channel model, and its performance was one of the best among the considered algorithms [40].…”

Section: Teager Kaisermentioning

confidence: 99%

Advanced Multipath Mitigation Techniques for Satellite-Based Positioning Applications

Bhuiyan

Lohan

2010

International Journal of Navigation and Observation

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Multipath remains a dominant source of ranging errors in Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS) or the future European satellite navigation system Galileo. Multipath is generally considered undesirable in the context of GNSS, since the reception of multipath can make significant distortion to the shape of the correlation function used for time delay estimation. However, some wireless communications techniques exploit multipath in order to provide signal diversity though in GNSS, the major challenge is to effectively mitigate the multipath, since we are interested only in the satellitereceiver transit time offset of the Line-Of-Sight (LOS) signal for the receiver's position estimate. Therefore, the multipath problem has been approached from several directions in order to mitigate the impact of multipath on navigation receivers, including the development of novel signal processing techniques. In this paper, we propose a maximum likelihood-based technique, namely, the Reduced Search Space Maximum Likelihood (RSSML) delay estimator, which is capable of mitigating the multipath effects reasonably well at the expense of increased complexity. The proposed RSSML attempts to compensate the multipath error contribution by performing a nonlinear curve fit on the input correlation function, which finds a perfect match from a set of ideal reference correlation functions with certain amplitude(s), phase(s), and delay(s) of the multipath signal. It also incorporates a threshold-based peak detection method, which eventually reduces the code-delay search space significantly. However, the downfall of RSSML is the memory requirement which it uses to store the reference correlation functions. The multipath performance of other delay-tracking methods previously studied for Binary Phase Shift Keying-(BPSK-) and Sine Binary Offset Carrier-(SinBOC-) modulated signals is also analyzed in closed loop model with the new Composite BOC (CBOC) modulation chosen for Galileo E1 signal. The simulation results show that the RSSML achieves the best multipath mitigation performance in a uniformly distributed two-to-four paths Rayleigh fading channel model for all three modulated signals.

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“…Many multipath estimation algorithms have been studied to eliminate the positioning error caused by multipath. Extended Kalman filter (EKF) is a useful algorithm for multipath estimation in Gaussian noises [1]. However, it cannot be effectively used to cope with multipath estimation problem with non-Gaussian noises.…”

Section: Introductionmentioning

confidence: 99%

Multipath estimation using an intelligent optimization algorithm with non-Gaussian noise

Cheng

Yue

Xie

et al. 2017

2017 23rd International Conference on Automation and Computing (ICAC)

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Abstract-Multipath is known to be one of the dominant error sources in high accuracy positioning systems, and multipath estimation is crucial for multipath mitigation. Most existing multipath estimation algorithms usually consider the cases of single mutlipath with Gaussian noise. However, non-Gaussian noises and two-multipath are often encountered in many practical environments. In this paper, a new algorithm is proposed to cope with the multipath estimation problem of the latter. First, the multipath estimation problem is transferred into a constrained optimization problem using the central error entropy criterion (CEEC) as its objective function. The second-order moment of the estimation error and the prior information are taken as constraints to reduce the mean of the estimation error. Then, a modified ε-constrained rank-based differential evolution (εRDE) algorithm is explored to solve the optimization problem. The proposed algorithm has been compared with the particle filter algorithm using a twomultipath case study example with non-Gaussian noises. The results suggest the proposed algorithm has improved the multipath estimation accuracy.

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Highly efficient techniques for mitigating the effects of multipath propagation in DS-CDMA delay estimation

Cited by 53 publications

References 34 publications

An advanced GNSS code multipath detection and estimation algorithm

An advanced GNSS code multipath detection and estimation algorithm

Advanced Multipath Mitigation Techniques for Satellite-Based Positioning Applications

Multipath estimation using an intelligent optimization algorithm with non-Gaussian noise

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