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Publications (10 of 322) Show all publications
Wahlström, J., Jaldén, J., Skog, I. & Händel, P. (2018). Alternative em Algorithms for Nonlinear State-Space Models. In: 2018 21st International Conference on Information Fusion, FUSION 2018: . Paper presented at 21st International Conference on Information Fusion, FUSION 2018, 10 July 2018 through 13 July 2018 (pp. 1260-1267). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Alternative em Algorithms for Nonlinear State-Space Models
2018 (English)In: 2018 21st International Conference on Information Fusion, FUSION 2018, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 1260-1267Conference paper, Published paper (Refereed)
Abstract [en]

The expectation-maximization algorithm is a commonly employed tool for system identification. However, for a large set of state-space models, the maximization step cannot be solved analytically. In these situations, a natural remedy is to make use of the expectation-maximization gradient algorithm, i.e., to replace the maximization step by a single iteration of Newton's method. We propose alternative expectation-maximization algorithms that replace the maximization step with a single iteration of some other well-known optimization method. These algorithms parallel the expectation-maximization gradient algorithm while relaxing the assumption of a concave objective function. The benefit of the proposed expectation-maximization algorithms is demonstrated with examples based on standard observation models in tracking and localization. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2018
Keywords
Expectation-maximization, Levenberg-Marquardt, system identification, the Gauss-Newton method, trust region, Identification (control systems), Image segmentation, Information fusion, Newton-Raphson method, Positron emission tomography, Religious buildings, Signal receivers, State space methods, Concave objective functions, Expectation - maximizations, Expectation-maximization algorithms, Gauss-Newton methods, Nonlinear state space models, State - space models, Maximum principle
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-236699 (URN)10.23919/ICIF.2018.8455234 (DOI)2-s2.0-85054096276 (Scopus ID)9780996452762 (ISBN)
Conference
21st International Conference on Information Fusion, FUSION 2018, 10 July 2018 through 13 July 2018
Funder
Swedish Foundation for Strategic Research
Note

Conference code: 139346; Export Date: 22 October 2018; Conference Paper; Funding details: SSF, Stiftelsen för Strategisk Forskning; Funding details: SSF, Sjögren’s Syndrome Foundation; Funding text: This research is financially supported by the Swedish Foundation for Strategic Research (SSF) via the project ASSEMBLE. QC 20181112

Available from: 2018-11-12 Created: 2018-11-12 Last updated: 2018-11-12Bibliographically approved
Händel, P. & Ronnow, D. (2018). Dirty MIMO Transmitters: Does It Matter?. IEEE Transactions on Wireless Communications, 17(8), 5425-5436
Open this publication in new window or tab >>Dirty MIMO Transmitters: Does It Matter?
2018 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 8, p. 5425-5436Article in journal (Refereed) Published
Abstract [en]

The radio frequency transmitter is a key component in contemporary multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing systems. A detailed study of a 2 x 2 MIMO transmitter subjected to correlated input data streams, nonlinear distortion, thermal noise, and crosstalk is provided by stochastic modeling. The effects of correlated input streams, crosstalk, and nonlinearities are studied in detail and exemplified both by approximate expressions and numerical simulations. Key results include exact and approximate expressions for the normalized mean-squared error (NMSE) for systems with or without digital predistortion; the relationship between NMSE and the signal-to-noise-and-distortion ratio, the properties of the distortion noise, and a novel design for power amplifier back-off for MIMO transmitters subject to crosstalk. The theoretical derivations are illustrated by numerical examples and simulation results, and their relationships to the state-of-the-art research are discussed.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Keywords
Orthogonal frequency division multiplexing (OFDM), input back-off, power amplifier, optimization, Bussgang theory
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-234629 (URN)10.1109/TWC.2018.2843764 (DOI)000441933900034 ()2-s2.0-85048562714 (Scopus ID)
Note

QC 20190913

Available from: 2018-09-13 Created: 2018-09-13 Last updated: 2018-09-13Bibliographically approved
Khan, Z. A., Zenteno, E., Händel, P. & Isaksson, M. (2018). Extraction of the Third-Order 3x3 MIMO VolterraKernel Outputs Using Multitone Signals. IEEE transactions on microwave theory and techniques, 66(11), 4985-4999
Open this publication in new window or tab >>Extraction of the Third-Order 3x3 MIMO VolterraKernel Outputs Using Multitone Signals
2018 (English)In: IEEE transactions on microwave theory and techniques, ISSN 0018-9480, E-ISSN 1557-9670, Vol. 66, no 11, p. 4985-4999Article in journal (Refereed) Published
Abstract [en]

This paper uses multitone signals to simplify theanalysis of 3×3 multiple-input multiple-output (MIMO) Volterrasystems by isolating the third-order kernel outputs from eachother. Multitone signals fed to an MIMO Volterra system yielda spectrum that is a permutation of the sums of the inputsignal tones. This a priori knowledge is used to design multitonesignals such that the third-order kernel outputs are isolated inthe frequency domain. The signals are designed by deriving theconditions for the offset and spacing of the input frequency grids.The proposed technique is then validated for the six possibleconfigurations of a 3x3 RF MIMO transmitter impaired bycrosstalk effects. The proposed multitone signal design is usedto extract the third-order kernel outputs, and their relativecontributions are analyzed to determine the dominant crosstalkeffects for each configuration.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-233974 (URN)10.1109/TMTT.2018.2854186 (DOI)000449354500028 ()
Note

QC 20180904

Available from: 2018-09-01 Created: 2018-09-01 Last updated: 2018-11-26Bibliographically approved
Wahlström, J., Skog, I., Nordström, R. L. & Händel, P. (2018). Fusion of OBD and GNSS Measurements of Speed. IEEE Transactions on Instrumentation and Measurement, 67(7), 1659-1667
Open this publication in new window or tab >>Fusion of OBD and GNSS Measurements of Speed
2018 (English)In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662, Vol. 67, no 7, p. 1659-1667Article in journal (Refereed) Published
Abstract [en]

There are two primary sources of sensor measurements for driver behavior profiling within insurance telematics and fleet management. The first is the on-board diagnostics system, typically found within most modern cars. The second is the global navigation satellite system, whose associated receivers commonly are embedded into smartphones or off-the-shelf telematics devices. In this paper, we present maximum likelihood and maximum a posteriori estimators for the problem of fusing speed measurements from these two sources to jointly estimate a vehicle's speed and the scale factor of the wheel speed sensors. In addition, we analyze the performance of the estimators by use of the Cramer-Rao bound, and discuss the estimation of model parameters describing measurement errors and vehicle dynamics. Last, simulations and real-world data are used to show that the proposed estimators yield a substantial performance gain compared to when employing only one of the two measurement sources.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018
Keywords
Driver behavior profiling, fleet management, global navigation satellite system (GNSS), insurance telematics, on-board diagnostics (OBD)
National Category
Control Engineering Vehicle Engineering
Identifiers
urn:nbn:se:kth:diva-231179 (URN)10.1109/TIM.2018.2803998 (DOI)000434457600016 ()2-s2.0-85042872129 (Scopus ID)
Note

QC 20180720

Available from: 2018-07-20 Created: 2018-07-20 Last updated: 2018-07-20Bibliographically approved
Wahlström, J., Skog, I. & Händel, P. (2018). Inertial Sensor Array Processing with Motion Models. In: 2018 21st International Conference on Information Fusion, FUSION 2018: . Paper presented at 21st International Conference on Information Fusion, FUSION 2018, 10 July 2018 through 13 July 2018 (pp. 788-793). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Inertial Sensor Array Processing with Motion Models
2018 (English)In: 2018 21st International Conference on Information Fusion, FUSION 2018, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 788-793Conference paper, Published paper (Refereed)
Abstract [en]

By arranging a large number of inertial sensors in an array and fusing their measurements, it is possible to create inertial sensor assemblies with a high performance-to-price ratio. Recently, a maximum likelihood estimator for fusing inertial array measurements collected at a given sampling instance was developed. In this paper, the maximum likelihood estimator is extended by introducing a motion model and deriving a maximum a posteriori estimator that jointly estimates the array dynamics at multiple sampling instances. Simulation examples are used to demonstrate that the proposed sensor fusion method have the potential to yield significant improvements in estimation accuracy. Further, by including the motion model, we resolve the sign ambiguity of gyro-free implementations, and thereby open up for implementations based on accelerometer-only arrays.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2018
Keywords
Inertial navigation systems, Information fusion, Maximum likelihood estimation, Array measurements, Inertial sensor, Maximum a Posteriori Estimator, Maximum likelihood estimator, Motion modeling, Multiple sampling, Sign ambiguities, Simulation example, Array processing
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-236701 (URN)10.23919/ICIF.2018.8455269 (DOI)2-s2.0-85054060306 (Scopus ID)9780996452762 (ISBN)
Conference
21st International Conference on Information Fusion, FUSION 2018, 10 July 2018 through 13 July 2018
Funder
Swedish Foundation for Strategic Research
Note

Conference code: 139346; Export Date: 22 October 2018; Conference Paper; Funding details: SSF, Stiftelsen för Strategisk Forskning; Funding details: SSF, Sjögren’s Syndrome Foundation; Funding text: This research is financially supported by the Swedish Foundation for Strategic Research (SSF) via the project ASSEMBLE.

Available from: 2018-11-12 Created: 2018-11-12 Last updated: 2018-11-12Bibliographically approved
Venkitaraman, A., Chatterjee, S. & Händel, P. (2018). MULTI-KERNEL REGRESSION FOR GRAPH SIGNAL PROCESSING. In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP): . Paper presented at 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) (pp. 4644-4648). IEEE
Open this publication in new window or tab >>MULTI-KERNEL REGRESSION FOR GRAPH SIGNAL PROCESSING
2018 (English)In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE, 2018, p. 4644-4648Conference paper, Published paper (Refereed)
Abstract [en]

We develop a multi-kernel based regression method for graph signal processing where the target signal is assumed to be smooth over a graph. In multi-kernel regression, an effective kernel function is expressed as a linear combination of many basis kernel functions. We estimate the linear weights to learn the effective kernel function by appropriate regularization based on graph smoothness. We show that the resulting optimization problem is shown to be convex and propose an accelerated projected gradient descent based solution. Simulation results using real-world graph signals show efficiency of the multi-kernel based approach over a standard kernel based approach.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Graph signal processing, kernel regression, convex optimization
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-237154 (URN)10.1109/ICASSP.2018.8461643 (DOI)000446384604162 ()2-s2.0-85054280684 (Scopus ID)
Conference
2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Note

QC 20181025

Available from: 2018-10-25 Created: 2018-10-25 Last updated: 2018-10-25Bibliographically approved
Yajnanarayana, V. & Händel, P. (2018). Performance evaluation of IR-UWB detectors and fusion techniques for UWB transceiver platforms. International Journal of Ultra Wideband Communications and Systems, 3(4), 177-191
Open this publication in new window or tab >>Performance evaluation of IR-UWB detectors and fusion techniques for UWB transceiver platforms
2018 (English)In: International Journal of Ultra Wideband Communications and Systems, ISSN 1758-728X, Vol. 3, no 4, p. 177-191Article in journal (Refereed) Published
Abstract [en]

In this paper, we analyse the performance of a multi-pulse impulse radio based ultra-wideband (IR-UWB) detector in an AWGN setting and provide different fusion strategies for fusing these detector outputs. To enable the transceiver to be used for multiple applications, the designers have different types of detectors such as energy detectors, amplitude detectors, etc., built in to a single transceiver architecture. In this paper, we derive the detection performance equation for commonly used detectors in terms of false alarm rate, shape of the pulse, and number of UWB pulses used in the detection and apply these in the fusion algorithms. We show that the performance can be improved by approximately 4 dB in terms of signal to noise ratio (SNR) for high probability of detection of a UWB signal (95%), by fusing decisions from multiple detector types compared to a standalone energy detector, in a practical scenario.

Place, publisher, year, edition, pages
Inderscience Enterprises Ltd., 2018
Keywords
Neyman-Pearson test, Sensor networks, Time of arrival, TOA, Ultra wideband, UWB, UWB ranging
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-238358 (URN)10.1504/IJUWBCS.2018.092426 (DOI)2-s2.0-85048791037 (Scopus ID)
Note

QC 20181031

Available from: 2018-10-31 Created: 2018-10-31 Last updated: 2018-10-31Bibliographically approved
Amin, S., Landin, P. N., Händel, P. & Rönnow, D. (2017). 2D Extended envelope memory polynomial model for concurrent dual-band RF transmitters. International journal of microwave and wireless technologies, 9(8), 1619-1627
Open this publication in new window or tab >>2D Extended envelope memory polynomial model for concurrent dual-band RF transmitters
2017 (English)In: International journal of microwave and wireless technologies, ISSN 1759-0795, E-ISSN 1759-0787, Vol. 9, no 8, p. 1619-1627Article in journal (Refereed) Published
Abstract [en]

The paper presents a two-dimensional (2D) extended envelope memory polynomial model for concurrent dual-band radio frequency (RF) power amplifiers (PAs). The model is derived based on the physical knowledge of a dual-band RF PA. The derived model contains cross-modulation terms not included in previously published models; these terms are found to be of importance for both behavioral modeling and digital predistortion (DPD). The performance of the derived model is evaluated both as the behavioral model and DPD, and the performance is compared with state-of-the-art 2D-DPD and dual-band generalized memory polynomial (DB-GMP) models. Experimental result shows that the proposed model resulted in normalized mean square error of -51.7/-51.6 dB and adjacent channel error power ratio of -63.1/-63.4 dB, for channel 1/2, whereas the 2D-DPD resulted in the largest model error and DB-GMP resulted in model parameters that are three times more than those resulted with the proposed model with the same performance. As pre-distorter, the proposed model resulted in adjacent channel power ratio of -55.8/-54.6 dB for channel 1/2 and is 7-10 dB lower than those resulted with the 2D-DPD model and 2-4 dB lower compared with the DB-GMP model.

Place, publisher, year, edition, pages
Cambridge University Press, 2017
Keywords
Power Amplifiers, RF Front-ends, Behavioral modeling and digital predistortion of multi-band amplifiers
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-221397 (URN)10.1017/S1759078717000277 (DOI)000418998100010 ()2-s2.0-85018373558 (Scopus ID)
Note

QC 20180117

Available from: 2018-01-17 Created: 2018-01-17 Last updated: 2018-01-17Bibliographically approved
Khan, Z. A., Händel, P. & Isaksson, M. (2017). A Comparative Analysis of the Complexity/Accuracy Tradeoff in the Mitigation of RF MIMO Transmitter Impairments. In: 89th ARFTG Microwave Measurement Conference: Advanced Technologies for Communications, ARFTG 2017: . Paper presented at 89th ARFTG Microwave Measurement Conference, ARFTG 2017; Ala Moana Hotel, Honolulu; United States; 9 June 2017 through. Institute of Electrical and Electronics Engineers (IEEE), Article ID 8000827.
Open this publication in new window or tab >>A Comparative Analysis of the Complexity/Accuracy Tradeoff in the Mitigation of RF MIMO Transmitter Impairments
2017 (English)In: 89th ARFTG Microwave Measurement Conference: Advanced Technologies for Communications, ARFTG 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, article id 8000827Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a comparative analysis of the complexity accuracy tradeoff in state-of-the-art RF MIMO transmitter mitigation models. The complexity and accuracy of the candidate models depends on the basis functions considered in these models. Therefore, a brief description of the mitigation models is presented accompanied by derivations of the model complexities in terms of the number of FLOPs. Consequently, the complexity accuracy tradeoff in the candidate models is evaluated for a 2 × 2 RF MIMO transmitter. Furthermore, the model complexities are analyzed for increasing nonlinear orders and number of antennas.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-210023 (URN)10.1109/ARFTG.2017.8000827 (DOI)2-s2.0-85030244336 (Scopus ID)9781538627471 (ISBN)
Conference
89th ARFTG Microwave Measurement Conference, ARFTG 2017; Ala Moana Hotel, Honolulu; United States; 9 June 2017 through
Note

QC 20170628

Available from: 2017-06-27 Created: 2017-06-27 Last updated: 2017-11-30Bibliographically approved
Wahlström, J., Skog, I., Händel, P., Khosrow-Khavar, F., Tavakolian, K., Stein, P. K. & Nehorai, A. (2017). A Hidden Markov Model for Seismocardiography. IEEE Transactions on Biomedical Engineering, 64(10), 2361-2372
Open this publication in new window or tab >>A Hidden Markov Model for Seismocardiography
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2017 (English)In: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 64, no 10, p. 2361-2372Article in journal (Refereed) Published
Abstract [en]

We propose a hidden Markov model approach for processing seismocardiograms. The seismocardiogram morphology is learned using the expectation-maximization algorithm, and the state of the heart at a given time instant is estimated by the Viterbi algorithm. From the obtained Viterbi sequence, it is then straightforward to estimate instantaneous heart rate, heart rate variability measures, and cardiac time intervals (the latter requiring a small number of manual annotations). As is shown in the conducted experimental study, the presented algorithm outperforms the state-of-the-art in seismocardiogram-based heart rate and heart rate variability estimation. Moreover, the isovolumic contraction time and the left ventricular ejection time are estimated with mean absolute errors of about 5 [ms] and 9 [ms], respectively. The proposed algorithm can be applied to any set of inertial sensors; does not require access to any additional sensor modalities; does not make any assumptions on the seismocardiogram morphology; and explicitly models sensor noise and beat-to-beat variations (both in amplitude and temporal scaling) in the seismocardiogram morphology. As such, it is well suited for low-cost implementations using off-the-shelf inertial sensors and targeting, e.g., at-home medical services.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2017
Keywords
Cardiac time intervals, heart rate variability (HRV), hidden Markov model (HMM), seismocardiogram (SCG)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-215801 (URN)10.1109/TBME.2017.2648741 (DOI)000411585100006 ()28092512 (PubMedID)2-s2.0-85026447100 (Scopus ID)
Note

QC 20171018

Available from: 2017-10-18 Created: 2017-10-18 Last updated: 2017-10-18Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2718-0262

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