| 1. |
- Adalbjörnsson, Stefan Ingi, et al.
(författare)
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Multi-Pitch Estimation Exploiting Block Sparsity
- 2015
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 109:April, s. 236-247
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Tidskriftsartikel (refereegranskat)abstract
- We study the problem of estimating the fundamental frequencies of a signal containing multiple harmonically related sinusoidal components using a novel block sparse signal representation. An efficient algorithm for solving the resulting optimization problem is devised exploiting a novel variable step-size alternating direction method of multipliers (ADMM). The resulting algorithm has guaranteed convergence and shows notable robustness to the f 0 vs f0/2f0/2 ambiguity problem. The superiority of the proposed method, as compared to earlier presented estimation techniques, is demonstrated using both simulated and measured audio signals, clearly indicating the preferable performance of the proposed technique.
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| 2. |
- Azizzadeh, Azad, et al.
(författare)
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BER performance analysis of coarsely quantized uplink massive MIMO
- 2019
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Ingår i: Signal Processing. - : ELSEVIER. - 0165-1684 .- 1872-7557. ; 161, s. 259-267
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Tidskriftsartikel (refereegranskat)abstract
- Having lower quantization resolution, has been introduced in the literature, to reduce the power consumption of massive MIMO and millimeter wave MIMO systems. Here, we analyze the bit error rate (BER) performance of quantized uplink massive MIMO employing few-bit resolution ADCs. Considering ZF detection, we derive a signal-to-interference, quantization and noise ratio (SIQNR) to achieve an analytical BER approximation for coarsely quantized M-QAM massive MIMO systems, by using a linear quantization model. The proposed expression is a function of the quantization resolution in bits. We further numerically investigate the effects of different quantization levels, from 1-bit to 4-bits, on the BER of three modulation types QPSK, 16-QAM, and 64-QAM. The uniform and non-uniform quantizers are employed in our simulation. Monte Carlo simulation results reveal that our approximate formula gives a tight upper bound on the BER performance of b-bit resolution quantized systems using non-uniform quantizers, whereas the use of uniform quantizers cause a lower performance. We also found a small BER performance degradation in coarsely quantized systems, for example 2-3 bits QPSK and 3-4 bits 16-QAM, compared to the full-precision (unquantized) case. However, this performance degradation can be compensated by increasing the number of antennas at the BS. (C) 2019 Published by Elsevier B.V.
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| 3. |
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| 4. |
- Brynolfsson, Johan, et al.
(författare)
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Parameter estimation of Oscillating Gaussian functions using the scaled reassigned spectrogram
- 2018
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 150, s. 20-32
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Tidskriftsartikel (refereegranskat)abstract
- In this paper we suggest an algorithm for estimation of the parameters detailing Oscillating Gaussian functions. The different components of the signal are first detected in the spectrogram. After this we exploit the fact that a Gaussian function may be perfectly reassigned into one single point given a correct scaling factor, where this scaling factor is a function of the unknown shape parameter of the Gaussian function. The scaled reassignment of the spectrogram is performed using a set of candidate scaling factors and the local Renyi entropy is used to measure the concentration of each component using every candidate scaling factor. The estimates are refined by using non-linear least squares. The algorithm is evaluated on both simulated and real data.
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| 5. |
- Burgess, Simon, et al.
(författare)
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TOA sensor network self-calibration for receiver and transmitter spaces with difference in dimension
- 2015
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 107:Online 11 June 2014, s. 33-42
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Tidskriftsartikel (refereegranskat)abstract
- We study and solve the previously unstudied problem of finding both transmitter and receiver positions using only time of arrival (TOA) measurements when there is a difference in dimensionality between the affine subspaces spanned by receivers and transmitters. Anchor-free TOA network calibration has uses both in radio, radio strength and sound applications, such as calibrating ad hoc microphone arrays. Using linear techniques and requiring only minimal number of receivers and transmitters, an algorithm is constructed for general dimension p for the lower dimensional subspace. Degenerate cases are determined and partially characterized as when receivers or transmitters inhabit a lower dimensional affine subspace than was given as input. The algorithm is further extended to overdetermined cases in a straightforward manner. Utilizing the minimal solver, an algorithm using the Random Sample Consensus (RANSAC) paradigm has been constructed to simultaneously solve the calibration problem and remove severe outliers, a common problem in TOA applications. Simulated experiments show good performance for the minimal solver and the RANSAC-like algorithm under noisy measurements. Two indoor environment experiments using microphones and speakers give a RMSE of 2.35 cm and 3.95 cm on receiver and transmitter positions compared to computer vision reconstructions.
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| 6. |
- Einemo, Martin, et al.
(författare)
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Weighted least squares algorithm for target localization in distributed MIMO radar
- 2015
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 115, s. 144-150
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we address the problem of locating a target using multiple-input multiple-output (MIMO) radar with widely separated antennas. Through linearizing the bistatic range measurements, which correspond to the sum of transmitter-to-target and target-to-receiver distances, a quadratically constrained quadratic program (QCQP) for target localization is formulated. The solution of the QCQP is proved to be an unbiased position estimate whose variance equals the Cramer-Rao lower bound. A weighted least squares algorithm is developed to realize the QCQP. Simulation results are included to demonstrate the high accuracy of the proposed MIMO radar positioning approach.
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| 7. |
- Elvander, Filip, et al.
(författare)
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An Adaptive Penalty Multi-Pitch Estimator with Self-Regularization
- 2016
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 127, s. 56-70
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Tidskriftsartikel (refereegranskat)abstract
- This work treats multi-pitch estimation, and in particular the common misclassification issue wherein the pitch at half the true fundamental frequency, the sub-octave, is chosen instead of the true pitch. Extending on current group LASSO-based methods for pitch estimation, this work introduces an adaptive total variation penalty, which enforces both group- and block sparsity, as well as deals with errors due to sub-octaves. Also presented is a scheme for signal adaptive dictionary construction and automatic selection of the regularization parameters. Used together with this scheme, the proposed method is shown to yield accurate pitch estimates when evaluated on synthetic speech data. The method is shown to perform as good as, or better than, current state-of-the-art sparse methods while requiring fewer tuning parameters than these, as well as several con- ventional pitch estimation methods, even when these are given oracle model orders. When evaluated on a set of ten musical pieces, the method shows promising results for separating multi-pitch signals.
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| 8. |
- Elvander, Filip, et al.
(författare)
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Multi-dimensional grid-less estimation of saturated signals
- 2018
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 145, s. 37-47
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Tidskriftsartikel (refereegranskat)abstract
- This work proposes a multi-dimensional frequency and amplitude estimator tailored for noise corrupted signals that have been clipped. Formulated as a sparse reconstruction problem, the proposed algorithm estimates the signal parameters by solving an atomic norm minimization problem. The estimator also exploits the waveform information provided by the clipped samples, incorporated in the form of linear constraints that have been augmented by slack variables as to provide robustness to noise. Numerical examples indicate that the algorithm offers preferable performance as compared to methods not exploiting the saturated samples.
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| 9. |
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| 10. |
- Gholami, Mohammad Reza, et al.
(författare)
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On geometric upper bounds for positioning algorithms in wireless sensor networks
- 2015
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 111, s. 179-193
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Tidskriftsartikel (refereegranskat)abstract
- This paper studies the possibility of upper bounding the position error for range-based positioning algorithms in wireless sensor networks. In this study, we argue that in certain situations when the measured distances between sensor nodes have positive errors, e.g., in non-line-of-sight (NLOS) conditions, the target node is confined to a closed bounded convex set (a feasible set) which can be derived from the measurements. Then, we formulate two classes of geometric upper bounds with respect to the feasible set. If an estimate is available, either feasible or infeasible, the position error can be upper bounded as the maximum distance between the estimate and any point in the feasible set (the first bound). Alternatively, if an estimate given by a positioning algorithm is always feasible, the maximum length of the feasible set is an upper bound on position error (the second bound). These bounds are formulated as nonconvex optimization problems. To progress, we relax the nonconvex problems and obtain convex problems, which can be efficiently solved. Simulation results show that the proposed bounds are reasonably tight in many situations, especially for NLOS conditions.
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