A Hybrid Positioning Method Based on Hypothesis Testing

Amiot, Nicolas; Pedersen, Troels; Laaraiedh, Mohamed; Uguen, Bernard

doi:10.1109/wcl.2012.051712.120131

Cited by 9 publications

(6 citation statements)

References 8 publications

(5 reference statements)

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“…The vertical distance between any two adjacent UCAs is h R . The array response vector can be given by a R,n (ϕ R,l , θ R,l ) = a RV,n (θ R,l ) ⊗ a RH,n (ϕ R,l , θ R,l ), (3) where…”

Section: System and Channel Modelsmentioning

confidence: 99%

“…Most of the existing positioning methods, e.g., [1], [3], [4], consider a narrowband channel model, and hence their algorithms could become ineffective in the practical systems where resolvable multipath signals in the temporal domain are present. Extension of these narrowband-based positioning methods to wideband systems is generally not straightforward, because channel parameters, e.g., signal subspace and steering matrices, actually vary with the carrier frequency [5].…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, most of the positioning algorithms proposed for mmWave massive MIMO systems, such as [3], [4], [8], [9], assume that the line-of-sight (LOS) path exists between mobile station (MS) and base station (BS), and they only focused on two-dimension (2D) scenarios. In practice, the LOS path may not exist, especially in dense urban and indoor environments.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

3D Wideband mmWave Localization for 5G Massive MIMO Systems

Lin¹,

Lv²,

Zhang³

et al. 2019

2019 IEEE Global Communications Conference (GLOBECOM)

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This paper proposes a novel 3D localization method for wideband mmWave massive MIMO systems. A high dimensional linear interpolation (HDLI)-based preprocessing is first proposed to transform the frequency-associated dynamical array response vectors into the common counterparts at the reference frequency. Through this method, the received data in all frequency bands can be processed jointly, and thus the high temporal resolution provided by wideband mmWave systems can be fully exploited for position estimation. To reduce the computational complexity in the process of the parameter estimation, we then present a wideband beamspace (WBS)based parameter estimation algorithm to estimate the angle and delay in the low-dimensional beamspace. By exploiting the quasi-optical propagation at the mmWave frequencies, a novel positioning scheme is also designed to determine the 3D location of the target. According to our analysis and simulation results, the proposed method is capable of achieving significantly reduced computational complexity, while maintaining high localization accuracy.

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“…The vertical distance between any two adjacent UCAs is h R . The array response vector can be given by a R,n (ϕ R,l , θ R,l ) = a RV,n (θ R,l ) ⊗ a RH,n (ϕ R,l , θ R,l ), (3) where…”

Section: System and Channel Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

3D Wideband mmWave Localization for 5G Massive MIMO Systems

Lin¹,

Lv²,

Zhang³

et al. 2019

2019 IEEE Global Communications Conference (GLOBECOM)

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show abstract

“…Açık literatürde hipotez testlerinin tasarımı konusunda bayağı fazla sayıda çalışma olduğundan (daha fazla detay için bkz. [35][36][37]) bu konu mevcut çalışma kapsamının dışında tutulmuş ve kanalın durumunun hassas bir şekilde tespit edilebildiği varsayılarak mesafe ölçümlerindeki hatanın azaltılması ve bunun da lokalizasyon algoritmalarının performansı üzerindeki etkileri irdelenmiştir.…”

Section: şEkil 7 Hata Kestirimi Ile Lokalizasyon Algoritmasının Geneunclassified

Mobi̇l Robotlarin Bi̇na İçi̇ Koşullarda Ulaşma Zamani Kullanilarak Kablosuz Lokali̇zasyonu

Kanaan

Kuş

2018

Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi

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Bu çalışma bina içi koşullarda çalışmak durumunda olan mobil robotların ulaşma zamanı tekniği kullanılarak kablosuz lokalizasyonu hakkındadır. Binanın içinde belli noktalarda konumlandırılmış referans noktaları vasıtası ile robotun bu noktalara olan mesafesinin ulaşma zamanı metodu ile tespiti ve buna bağlı olarak robotun konumunun tespiti (lokalizasyonu) hedeflenmektedir. Çalışmanın literatüre somut katkıları şu şekilde özetlenebilir. İlk olarak mobil robotun referans noktalarına göre hareketi sonucu değişen kanal koşullarına bağlı olarak değişken mesafe ölçüm hatalarının olduğu durumlarda iki farklı lokalizasyon algoritmasının (en küçük kareler ve ağırlıklı en küçük kareler) performansları karşılaştırmalı olarak analiz edilmiştir. İkinci olarak mesafe ölçümlerindeki hataları mesafe ölçümleri lokalizasyon algoritmaları tarafından kullanılmadan önce azaltmayı hedefleyen bir hata kestirim metodu önerilmiş, bahsedilen lokalizasyon algoritmalarının performansı bu metot ile beraber analiz edilmiştir. Elde edilen sonuçlar hata kestirim metodu ile beraber kullanıldığında her iki algoritmanın performansının sistem senaryolarına bağlı olarak %5-17 oranında iyileştirilebileceğini göstermektedir.

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“…Based on different type of measurements, the common localization methods estimate the source position using time of arrival (TOA), time difference of arrival (TDOA), angle of arrival (AOA), Doppler frequency, Fingerprint and received signal strength (RSS) [5][6][7][8][9][10][11][12][13]. To improving the accuracy further, a series of hybrid method is developed by combining several kinds of measurements [14][15][16]. Since TOA localization has the precision advantage in position estimate, particularly in indoor environments [17], it attracts much interest in the netted mono-static radar, multi-static radar and distributed multi-input multi-output (MIMO) system.…”

Section: Introductionmentioning

confidence: 99%

Refinement of TOA Localization with Sensor Position Uncertainty in Closed-Form

Gan¹,

Cong²,

Sun

2020

Sensors

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The subject of localization has received great deal attention in the past decades. Although it is perhaps a well-studied problem, there is still room for improvement. Traditional localization methods usually assume the number of sensors is sufficient for providing desired performance. However, this assumption is not always satisfied in practice. This paper studies the time of arrival (TOA)-based source positioning in the presence of sensor position errors. An error refined solution is developed for reducing the mean-squared-error (MSE) and bias in small sensor network (the number of sensors is fewer) when the noise or error level is relatively large. The MSE performance is analyzed theoretically and validated by simulations. Analytical and numerical results show the proposed method attains the Cramér-Rao lower bound (CRLB). It outperforms the existing closed-form methods with slightly raising computation complexity, especially in the larger noise/error case.

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A Hybrid Positioning Method Based on Hypothesis Testing

Cited by 9 publications

References 8 publications

3D Wideband mmWave Localization for 5G Massive MIMO Systems

3D Wideband mmWave Localization for 5G Massive MIMO Systems

Mobi̇l Robotlarin Bi̇na İçi̇ Koşullarda Ulaşma Zamani Kullanilarak Kablosuz Lokali̇zasyonu

Refinement of TOA Localization with Sensor Position Uncertainty in Closed-Form

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