Efficient Maximum Likelihood Joint Estimation of Angles and Times of Arrival of Multiple Paths

Bazzi, Ahmad; Slock, Dirk; Meilhac, Lisa

doi:10.1109/glocomw.2015.7414203

Cited by 29 publications

(18 citation statements)

References 25 publications

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“…However, they suffer from exhaustive computational burden as they require a 𝑝𝐾-dimensional search, where 𝐾 and 𝑝 represent the number of impinged sources and the number of signal parameters to be estimated in each source. There have been several research efforts on developing computational attractive solutions for ML-based JADE methods [21], [28]- [31]. The first category transforms the complicated high-dimensional ML search into several successive low-dimensional search based on the idea of alternating minimization [28], [29] or expectation-maximization (EM) [21], [30]; while the second category derives a close-form solution for each ML iteration based on polynomial parameterizations [31].…”

Section: A Related Workmentioning

confidence: 99%

“…There have been several research efforts on developing computational attractive solutions for ML-based JADE methods [21], [28]- [31]. The first category transforms the complicated high-dimensional ML search into several successive low-dimensional search based on the idea of alternating minimization [28], [29] or expectation-maximization (EM) [21], [30]; while the second category derives a close-form solution for each ML iteration based on polynomial parameterizations [31]. The most widely used ML implementation in the first category is the spacealternating generalized EM (SAGE) method [32], which has been employed in [30] and [21] for JADE based on Wi-Fi signals and 5G signals, respectively.…”

Section: A Related Workmentioning

confidence: 99%

“…The most widely used ML implementation in the first category is the spacealternating generalized EM (SAGE) method [32], which has been employed in [30] and [21] for JADE based on Wi-Fi signals and 5G signals, respectively. As an example for the second category, [31] derives the 2-D iterative quadratic ML (IQML) algorithm [33] for JADE based on OFDM signals. Other polynomial parameterization methods for ML estimators can also be extended to solve the JADE problem [34].…”

Section: A Related Workmentioning

confidence: 99%

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Efficient Joint DOA and TOA Estimation for Indoor Positioning with 5G Picocell Base Stations

Pan,

Liu,

Liu

et al. 2022

Preprint

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The ubiquity, large bandwidth, and spatial diversity of the fifth generation (5G) cellular signal render it a promising candidate for accurate positioning in indoor environments where the global navigation satellite system (GNSS) signal is absent. In this paper, a joint angle and delay estimation (JADE) scheme is designed for 5G picocell base stations (gNBs) which addresses two crucial issues to make it both effective and efficient in realistic indoor environments. Firstly, the direction-dependence of the array modeling error for picocell gNB as well as its impact on JADE is revealed. This error is mitigated by fitting the array response measurements to a vector-valued function and pre-calibrating the ideal steering-vector with the fitted function. Secondly, based on the deployment reality that 5G picocell gNBs only have a small-scale antenna array but have a large signal bandwidth, the proposed scheme decouples the estimation of time-of-arrival (TOA) and direction-of-arrival (DOA) to reduce the huge complexity induced by two-dimensional joint processing. It employs the iterative-adaptive-approach (IAA) to resolve multipath signals in the TOA domain, followed by a conventional beamformer (CBF) to retrieve the desired line-of-sight DOA. By further exploiting a dimension-reducing pre-processing module and accelerating spectrum computing by fast Fourier transforms, an efficient implementation is achieved for real-time JADE. Numerical simulations demonstrate the superiority of the proposed method in terms of DOA estimation accuracy. Field tests show that a triangulation positioning error of 0.44 m is achieved for 90% cases using only DOAs estimated at two separated receiving points.Index Terms-Direction-of-arrival, time-of-arrival, JADE, array modeling errors, direction-dependent antenna error, efficient implementation, 5G. I. INTRODUCTIONL OCATION awareness plays a paramount role in a wealth of scenarios, such as autonomous driving [1], intelligent transportation [2], emergency relief [3], assisted living [4], etc., in the era of Internet-of-everything (IoE). In outdoor environments, the global navigation satellite systems (GNSS) provide robust and accurate positioning information, while in deep urban canyons and indoor environments, they are unreliable owing to the severe blockage of the line-of-sight (LOS) signals.

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Section: A Related Workmentioning

confidence: 99%

Section: A Related Workmentioning

confidence: 99%

Section: A Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Efficient Joint DOA and TOA Estimation for Indoor Positioning with 5G Picocell Base Stations

Pan,

Liu,

Liu

et al. 2022

Preprint

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“…where N = T obs T is the number of samples, c i,n the discrete symbol related to the n-th sample taken at t i,n = t i + nT , and ν i,n ∼ CN M (0, σ 2 I M ) the filtered thermal noise, with σ 2 denoting the noise power and I M the M × M identity matrix. We assume that the symbols are known to the receiver, which is usually obtained by considering the first part of the transmission where a known training sequence is inserted for channel estimation and synchronization purposes [32]. 5 Hereafter, we denote with…”

Section: System Modelmentioning

confidence: 99%

Mobile Positioning in Multipath Environments: a Pseudo Maximum Likelihood approach

Fascista,

Coluccia,

Ricci

2018

Preprint

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The problem of mobile position estimation in multipath scenarios is addressed. A low-complexity, fully-adaptive algorithm is proposed, based on the pseudo maximum likelihood approach. The processing is done exclusively on-board at the mobile node by exploiting narrowband downlink radio signals. The proposed algorithm is able to estimate via adaptive beamforming (with spatial smoothing) the optimal projection matrices that maximize the likelihood; in addition, it can associate the line-of-sight over the trajectory, hence achieving an integration gain. The performance assessment shows that the proposed algorithm is very effective in (even severe) multipath conditions, outperforming natural competitors also when the number of antennas and snapshots is kept at the theoretical minimum.

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“…Intuitively, since joint DOA and TD estimation simultaneously exploits the DOA and TD structure of the multipath channels, the corresponding CRB (18) should be lower than or at least equal to the CRB (21) for DOA-only estimation. This is theoretically verified by the following results.…”

Section: B Analysismentioning

confidence: 99%

Benefit of Joint DOA and Delay Estimation with Application to Indoor Localization in WiFi and 5G

Wen¹,

Liu²,

Wei³

et al. 2018

Preprint

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Accurate indoor localization has long been a challenging problem due to the presence of multipath. Joint directionof-arrival (DOA) and time delay (TD) estimation is a promising technique for accurate indoor Localization in next generation WiFi and 5G, as it has the capability of separating the lineof-sight (LOS) signal from multipath signals in the TD space. Although the benefit of joint DOA and TD estimation over DOA-only estimation has been empirically shown long ago, it has not been theoretically justified yet. In this paper, we provide a theoretical proof of the benefit of joint DOA and TD estimation over DOA-only estimation. Further, experimental results with simulated WiFi setting have been provided to demonstrate the theoretical finding. Matlab code is available at https://github.com/FWen/JADE.git.

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Efficient Maximum Likelihood Joint Estimation of Angles and Times of Arrival of Multiple Paths

Cited by 29 publications

References 25 publications

Efficient Joint DOA and TOA Estimation for Indoor Positioning with 5G Picocell Base Stations

Efficient Joint DOA and TOA Estimation for Indoor Positioning with 5G Picocell Base Stations

Mobile Positioning in Multipath Environments: a Pseudo Maximum Likelihood approach

Benefit of Joint DOA and Delay Estimation with Application to Indoor Localization in WiFi and 5G

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