Adaptive tracking of narrowband HF channel response

Arıkan, Feza; Arıkan, Orhan

doi:10.1029/2003rs002879

Cited by 3 publications

(4 citation statements)

References 5 publications

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“…The implementation of LS estimation algorithm is very cost effective and simple. From previous studies conducted at high signal to noise (SNR) ratios and for time invariant channels, it is observed that the LS method converges faster when compared to other methods such as the Kalman Filter [6,7]. However, for low SNR values or time-varying channels, the performance of LS method degrades significantly and does not form an alternative for channel estimation [6,7].…”

Section: Least Squares (Ls)mentioning

confidence: 93%

“…When the performance of the KF estimation algorithm is tested with the channel outputs obtained from simulated HF links under good, moderate and poor ionospheric conditions, it is observed that even for time-varying and/or severe channel conditions, where other algorithms such as the LS method fails, Kalman Filter still converges with a reasonable error and is capable of tracking the variations of the channel [6,7]. With the new state-space model to capture the pulseto-pulse variability of the channel impulse response and initialization, the tracking performance of the Kalman filter improved significantly compared to that of the Conventional Kalman Filter even under poor ionospheric conditions.…”

Section: Kalman Filtermentioning

confidence: 99%

“…The correlation function R u (n) of the noise in system dynamics plays a critical role in the overall performance of the Kalman channel estimator. We used a time-varying form for R u (n) which is chosen to reflect our experience on the actual time variation of HF channels, where the channel response shows greater variation in the vicinity of the peaks [6,7]. So, the innovative contribution to this estimation method is the choice of the initial conditions using least squares algorithm and representing the correlation of the variation on 844 Arikan the channel response adaptively from pulse to pulse as a function of past estimates of h(t; τ ) [6,7].…”

Section: Kalman Filtermentioning

confidence: 99%

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A Brief Review of HF Channel Response Estimation

Arıkan¹

2004

Journal of Electromagnetic Waves and Applications

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Estimation of channel impulse response constitutes a first step in computation of scattering function. Due to spatial and temporal variations, HF channel impulse response has to be estimated adaptively. The channel impulse response can be estimated using various estimators. In this paper, a brief review of standard estimation algorithms such as Least Squares, Least Mean Squares, Recursive Least Squares, Kalman Filter is presented. Then, an alternative estimation algorithm for the channel modulation response is proposed as a solution to a least squares constraint optimization problem. The proposed computation constrains the unknown channel impulse response to be a bandlimited function of time for a fixed delay. The new method is simple and cost-effective due to the fact that numerical computation is based on the correlation of the samples of estimated channel impulse response. After finding the optimal channel response estimate, further processing for equalization and detection can be achieved successfully.

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Section: Least Squares (Ls)mentioning

confidence: 93%

Section: Kalman Filtermentioning

confidence: 99%

Section: Kalman Filtermentioning

confidence: 99%

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A Brief Review of HF Channel Response Estimation

Arıkan¹

2004

Journal of Electromagnetic Waves and Applications

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“…Spacebased systems depend on systems such as Global Positioning System (GPS), GLONASS, and TOPEX/Poseidon. Since GPS is a global system and there are several Continuously Operating Receiver Stations (CORS) networks composed of hundreds of GPS receivers deployed both globally and also regionally such as International GNSS Stations (IGS), Regional Reference Frame Sub-Commission for Europe (EUREF), Turkish National Permanent GPS Network (TNPGN) Active, etc., TEC measurements from GPS signals is a widely used technique, [2]- [5].…”

Section: Introductionmentioning

confidence: 99%

Regional Total Electron Content Map Generation based on Compressive Sensing

Sunu,

Toker

2020

Preprint

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Ionosphere has an important role in long distance HF communications, satellite communications and global navigation systems. Ionosphere is a plasma medium which arises due to solar and cosmic radiation, and the amount of ionization is highly time and location dependent. Eventually, the current state of the ionosphere should be continuously monitored with high accuracy. Total Electron Content (TEC) maps are being used to investigate the state of the ionosphere. There are online services which provide TEC maps, however they mostly have low spatial and temporal resolution and the techniques used for generating these maps are generally not accessible.TEC maps can also be generated from GNSS/GPS based Continuously Operating Receiver Stations (CORS) network measurements. Unfortunately, the GNSS/GPS receiver networks are not dense enough to form a map directly. Therefore, an algorithm should be used to estimate the TEC values at coordinates without a receiver. Based on the observation that TEC maps possess a high degree of sparsity, we propose a modified compressive sensing technique for generating regional TEC maps by using the sparse dataset obtained from a CORS network.We evaluate the performance of the proposed technique both over synthetically generated TEC maps which mimic the common characteristics of the ionosphere, and also over actual measurements taken over the Turkish National Permanent GPS Network (TNPGN) Active. Our analysis reveals that the proposed technique can produce TEC maps with high accuracy and resolution. We also demonstrate the superiority of our technique over other TEC map generation techniques found in the literature.

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Multipath Separation-Direction of Arrival (MS-DOA) with Genetic Search Algorithm for HF channels

Arıkan

Köroğlu

Fidan

et al. 2009

Advances in Space Research

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Direction-of-Arrival (DOA) defines the estimation of arrival angles of an electromagnetic wave impinging on a set of sensors. For dispersive and time-varying HF channels, where the propagating wave also suffers from the multipath phenomena, estimation of DOA is a very challenging problem. Multipath Separation-Direction of Arrival (MS-DOA), that is developed to estimate both the arrival angles in elevation and azimuth and the incoming signals at the output of the reference antenna with very high accuracy, proves itself as a strong alternative in DOA estimation for HF channels. In MS-DOA, a linear system of equations is formed using the coefficients of the basis vector for the array output vector, the incoming signal vector and the array manifold. The angles of arrival in elevation and azimuth are obtained as the maximizers of the sum of the magnitude squares of the projection of the signal coefficients on the column space of the array manifold. In this study, alternative Genetic Search Algorithms (GA) for the maximizers of the projection sum are investigated using simulated and experimental ionospheric channel data. It is observed that GA combined with MS-DOA is a powerful alternative in online DOA estimation and can be further developed according to the channel characteristics of a specific HF link.

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Adaptive tracking of narrowband HF channel response

Cited by 3 publications

References 5 publications

A Brief Review of HF Channel Response Estimation

A Brief Review of HF Channel Response Estimation

Regional Total Electron Content Map Generation based on Compressive Sensing

Multipath Separation-Direction of Arrival (MS-DOA) with Genetic Search Algorithm for HF channels

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