| 1. |
- Bergström, Andreas, 1978-
(författare)
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Timing-Based Localization using Multipath Information
- 2020
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The measurements of radio signals are commonly used for localization purposes where the goal is to determine the spatial position of one or multiple objects. In realistic scenarios, any transmitted radio signal will be affected by the environment through reflections, diffraction at edges and corners etc. This causes a phenomenon known as multipath propagation, by which multiple instances of the transmitted signal having traversed different paths are heard by the receiver. These are known as Multi-Path Components (MPCs). The direct path (DP) between transmitter and receiver may also be occluded, causing what is referred to as non-Line-of-Sight (non-LOS) conditions. As a consequence of these effects, the estimated position of the object(s) may often be erroneous.This thesis focuses on how to achieve better localization accuracy by accounting for the above-mentioned multipath propagation and non-LOS effects. It is proposed how to mitigate these in the context of positioning based on estimation of the DP between transmitter and receiver. It is also proposed how to constructively utilize the additional information about the environment which they implicitly provide. This is all done in a framework wherein a given signal model and a map of the surroundings are used to build a mathematical model of the radio environment, from which the resulting MPCs are estimated.First, methods to mitigate the adverse effects of multipath propagation and non-LOS conditions for positioning based on estimation of the DP between transmitter and receiver are presented. This is initially done by using robust statistical measurement error models based on aggregated error statistics, where significant improvements are obtained without the need to provide detailed received signal information. The gains are seen to be even larger with up-to-date real-time information based on the estimated MPCs.Second, the association of the estimated MPCs with the signal paths predicted by the environmental model is addressed. This leads to a combinatorial problem which is approached with tools from multi-target tracking theory. A rich radio environment in terms of many MPCs gives better localization accuracy but causes the problem size to grow large—something which can be remedied by excluding less probable paths. Simulations indicate that in such environments, the single best association hypothesis may be a reasonable approximation which avoids the calculation of a vast number of possible hypotheses. Accounting for erroneous measurements is crucial but may have drawbacks if no such are occurring.Finally, theoretical localization performance bounds when utilizing all or a subset of the available MPCs are derived. A rich radio environment allows for good positioning accuracy using only a few transmitters/receivers, assuming that these are used in the localization process. In contrast, in a less rich environment where basically only the DP/LOS components are measurable, more transmitters/receivers and/or the combination of downlink and uplink measurements are required to achieve the same accuracy. The receiver’s capability of distinguishing between multiple MPCs arriving approximately at the same time also affects the localization accuracy.
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| 2. |
- Forsling, Robin, 1988-, et al.
(författare)
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Conservative Linear Unbiased Estimation Under Partially Known Covariances
- 2022
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Ingår i: IEEE Transactions on Signal Processing. - : IEEE. - 1053-587X .- 1941-0476. ; 70, s. 3123-3135
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Tidskriftsartikel (refereegranskat)abstract
- Mean square error optimal estimation requires the full correlation structure to be available. Unfortunately, it is not always possible to maintain full knowledge about the correlations. One example is decentralized data fusion where the cross-correlations between estimates are unknown, partly due to information sharing. To avoid underestimating the covariance of an estimate in such situations, conservative estimation is one option. In this paper the conservative linear unbiased estimator is formalized including optimality criteria. Fundamental bounds of the optimal conservative linear unbiased estimator are derived. A main contribution is a general approach for computing the proposed estimator based on robust optimization. Furthermore, it is shown that several existing estimation algorithms are special cases of the optimal conservative linear unbiased estimator. An evaluation verifies the theoretical considerations and shows that the optimization based approach performs better than existing conservative estimation methods in certain cases.
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| 3. |
- Gustafsson, Fredrik, 1964-, et al.
(författare)
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Sensor models and localization algorithms for sensor networks based on received signal strength
- 2012
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Ingår i: EURASIP Journal on Wireless Communications and Networking. - : Springer. - 1687-1472 .- 1687-1499. ; 1:16
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Tidskriftsartikel (refereegranskat)abstract
- Received signal strength (RSS) can be used in sensor networks as a ranging measurement for positioning and localization applications. This contribution studies the realistic situation where neither the emitted power nor the power law decay exponent be assumed to be known. The application in mind is a rapidly deployed network consisting of a number of sensor nodes with low-bandwidth communication, each node measuring RSS of signals traveled through air (microphones) and ground (geophones). The first contribution concerns validation of a model in logarithmic scale, that is, linear in the unknown nuisance parameters (emitted power and power loss constant). The parameter variation is studied over time and space. The second contribution is a localization algorithm based on this model, where the separable least squares principle is applied to the non-linear least squares (NLS) cost function, after which a cost function of only the unknown position is obtained. Results from field trials are presented to illustrate the method, together with fundamental performance bounds. The ambition is to pave the way for sensor configuration design and more thorough performance evaluations as well as filtering and target tracking aspects.
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| 4. |
- Kasebzadeh, Parinaz, 1985-
(författare)
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Parameter Estimation for Mobile Positioning Applications
- 2017
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The availability and reliability of mobile positioning algorithms depend on both the quality of measurements and the environmental characteristics. The positioning systems based on global navigation satellite systems (GNSS), for example, have typically a few meters accuracy but are unavailable in signal denied conditions and unreliable in multipath environments. Other radio network based positioning algorithms have the same drawbacks. This thesis considers a couple of cases where these drawbacks can be mitigated by model-based sensor fusion techniques.The received signal strength (RSS) is commonly used in cellular radio networks for positioning due to its high availability, but its reliability depends heavily on the environment. We have studied how the directional dependence in the antenna gain in the base stations can be compensated for. We propose a semiempirical model for RSS measurements, composed of an empirical log-distance model of the RSS decay rate, and a deterministic antenna gain model that accounts for non-uniform base station antenna radiation. Evaluations and comparisons presented in this study demonstrate an improvement in estimation performance of the joint model compared to the propagation model alone.Inertial navigation systems (INS ) rely on integrating inertial sensor measurements. INS as a standalone system is known to have a cubic drift in the position error, and it needs supporting sensor information, for instance, position fixes from GNSS whenever available. For pedestrians, special tricks such as parametric gait models and step detections can be used to limit the drift. In general, the more accurate gait parameters, the better position estimation accuracy. An improved pedestrian dead reckoning (PDR) algorithm is developed that learns gait parameters in time intervals when direct position measurements (such as GNSS positions) are available. We present a multi-rate filtering solution that leads to improved estimates of both gait parameters and position. To further extend the algorithm to more realistic scenarios, a joint classifier of the user’s motion and the device’s carrying mode is developed. Classification of motion mode (walking, running, standing still) and device mode (hand-held, in pocket, in backpack) provides information that can assist in the gait learning process and hence improve the position estimation. The algorithms are applied to collected data and promising results are reported. Furthermore, one of the most extensive datasets for personal navigation systems using both rigid body motion trackers and smartphones is presented, and this dataset has also been made publicly available.
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| 5. |
- Nielsen, Lars, 1955-, et al.
(författare)
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Issues in Diagnosis, Supervision, and Safety
- 1996
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Issues concerning diagnosis, supervision and saftey are found in many technologically advanced products. There is now a trend to extend the functionality of diagnosis and supervision systems to handle more advanced situations. This report collects some of the initiatives taking place in research and some of the developments taking place in the industry.
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| 6. |
- Radnosrati, Kamiar, 1987-
(författare)
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On Timing-Based Localization in Cellular Radio Networks
- 2018
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The possibilities for positioning in cellular networks has increased over time, pushed by increased needs for location based products and services for a variety of purposes. It all started with rough position estimates based on timing measurements and sector information available in the global system for mobile communication (gsm), and today there is an increased standardization effort to provide more position relevant measurements in cellular communication systems to improve on localization accuracy and availability. A first purpose of this thesis is to survey recent efforts in the area and their potential for localization. The rest of the thesis then investigates three particular aspects, where the focus is on timing measurements. How can these be combined in the best way in long term evolution (lte), what is the potential for the new narrow-band communication links for localization, and can the timing measurement error be more accurately modeled?The first contribution concerns a narrow-band standard in lte intended for internet of things (iot) devices. This lte standard includes a special position reference signal sent synchronized by all base stations (bs) to all iot devices. Each device can then compute several pair-wise time differences that corresponds to hyperbolic functions. Using multilateration methods the intersection of a set of such hyperbolas can be computed. An extensive performance study using a professional simulation environment with realistic user models is presented, indicating that a decent position accuracy can be achieved despite the narrow bandwidth of the channel.The second contribution is a study of how downlink measurements in lte can be combined. Time of flight (tof) to the serving bs and time difference of arrival (tdoa) to the neighboring bs are used as measurements. From a geometrical perspective, the position estimation problem involves computing the intersection of a circle and hyperbolas, all with uncertain radii. We propose a fusion framework for both snapshot estimation and filtering, and evaluate with both simulated and experimental field test data. The results indicate that the position accuracy is better than 40 meters 95% of the time.A third study in the thesis analyzes the statistical distribution of timing measurement errors in lte systems. Three different machine learning methods are applied to the experimental data to fit Gaussian mixture distributions to the observed measurement errors. Since current positioning algorithms are mostly based on Gaussian distribution models, knowledge of a good model for the measurement errors can be used to improve the accuracy and robustness of the algorithms. The obtained results indicate that a single Gaussian distribution is not adequate to model the real toa measurement errors. One possible future study is to further develop standard algorithms with these models.
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| 7. |
- Sundbom, Per, 1981-
(författare)
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Acoustic and afterload evaluation of left ventricular assist devices
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Background: Heart Failure is a serious condition with consequences not only for the individual patient but also for the society with a 5-year mortality rate of 45-60%, and a substantial economic burden. The estimated prevalence in Sweden is 2.2% and the age adjusted prevalence increases with higher age. The fundamental treatment for heart failure is pharmaceutical in combination with life-style changes, and physiotherapy. For patients with advanced heart failure, the use of long-term circulatory support can be an option as a bridge to transplantation, or as destination therapy. However, this treatment entails a risk of multiple adverse events. The incidence of pump thrombosis increased as a clinical problem in 2012 and the need for diagnostic methods were desired. The aim of this thesis was to develop and to evaluate the use of a mock loop circuit to study the acoustics of left ventricular assist devices, to evaluate different recording devices and to study the effect of afterload on pump function.Methods: Two different mock loops, with the possibility to insert artificial thrombus and to adjust preload and afterload were created to facilitate recording of the left ventricular assist devices. An iPhone/iPodTM was used as recording device since remote monitoring is desirable. The sounds from HeartMate IITM during different conditions were studied. The iPhone/iPod was evaluated in comparison to dedicated recording equipment, and the mock loop recordings to clinical situation. The sound from HeartMate 3TM was studied, compared between in vivo and in vitro recordings, and the use of an electronic stethoscope was evaluated. The impact of afterload on left ventricular assist devices was studied in a mock loop circuit with different changes in preload and afterload.Results: Mock loop circuit is a promising method to safely change the surrounding conditions as the pump is working. The sound from both HeartMate IITM and HeartMate 3TM can be recorded and analyzed in frequency and time domain. When inserting artificial thrombus in a HeartMate IITM the frequency spectrum is altered. The use of dedicated recording devices is superior to both electronic stethoscope and iPhone/iPodTM, but these handheld devices can be used in clinical settings. The recordings from mock loop circuit and patients appear similar for both HeartMate IITM and HeartMate 3TM. The flow of the devices is affected by the afterload. The HeartMate 3TM is more resistant to increased clot analogs within the pump. For both pumps, best efficacy is seen for clean circuits. The flow rate from the monitor might be misleading since the measured flow rate and the flow rate from monitor can differ due to surrounding conditions. The estimated flow might be adjusted by fitting a parabolic curve.Conclusion: The use of mock loop circuit to study both flow and sound under different conditions is valid. It is possible to record and study the sound from both HeartMate IITM and HeartMate 3TM. The sound holds information of pump function and appears similar in vivo and in vitro. All recording devices can be used, but dedicated equipment is superior to the more handheld devices, although these might have a function as a screening device. The flow measurement on the monitor might not be valid and optimization of fluid status and afterload can further increase pump efficiency.
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| 8. |
- Sundbom, Per, 1981-, et al.
(författare)
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Sound analysis of the magnetically levitated left ventricular assist device HeartMate 3™
- 2019
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Ingår i: International Journal of Artificial Organs. - : Sagamore Publishing. - 0391-3988 .- 1724-6040. ; 42:12, s. 717-724
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: The HeartMate 3™ has shown lower rates of adverse events compared to previous devices due to the design and absence of mechanical bearings. For previous devices, sound analysis emerged as a way to assess pump function. The aims of this study were to determine if sound analysis can be applied to the HeartMate 3 in vivo and in vitro and to evaluate an electronic stethoscope.METHOD: Sound recordings were performed with microphones and clinical accessible electronic stethoscope. The recordings were studied in both the time and the frequency domains. Recordings from four patients were performed to determine if in vivo and in vitro recordings are comparable.RESULTS: The results show that it is possible to detect sound from HeartMate 3 and the sound spectrum is clear. Pump frequency and frequency of the pulsatile mode are easily determined. Frequency spectra from in vitro and in vivo recordings have the same pattern, and the major proportion (96.7%) of signal power is located at the pump speed frequency ±40 Hz. The recordings from the patients show low inter-individual differences except from location of peaks originating from pump speed and harmonics. Electronic stethoscopes could be used for sound recordings, but the dedicated equipment showed a clearer sound spectrum.DISCUSSION: The results show that acoustic analysis can also be performed with the HeartMate 3 and that in vivo and in vitro sound spectrum is similar. The frequency spectra are different from previous devices, and methods for assessing pump function or thrombosis need further evaluation.
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| 9. |
- Zhao, Yuxin, 1986-
(författare)
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Gaussian Processes for Positioning Using Radio Signal Strength Measurements
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Estimation of unknown parameters is considered as one of the major research areas in statistical signal processing. In the most recent decades, approaches in estimation theory have become more and more attractive in practical applications. Examples of such applications may include, but are not limited to, positioning using various measurable radio signals in indoor environments, self-navigation for autonomous cars, image processing, radar tracking and so on. One issue that is usually encountered when solving an estimation problem is to identify a good system model, which may have great impacts on the estimation performance. In this thesis, we are interested in studying estimation problems particularly in inferring the unknown positions from noisy radio signal measurements. In addition, the modeling of the system is studied by investigating the relationship between positions and radio signal strength measurements.One of the main contributions of this thesis is to propose a novel indoor positioning framework based on proximity measurements, which are obtained by quantizing the received signal strength measurements. Sequential Monte Carlo methods, to be more specific particle filter and smoother, are utilized for estimating unknown positions from proximity measurements. The Cramér-Rao bounds for proximity-based positioning are further derived as a benchmark for the positioning accuracy in this framework.Secondly, to improve the estimation performance, Bayesian non-parametric modeling, namely Gaussian processes, have been adopted to provide more accurate and flexible models for both dynamic motions and radio signal strength measurements. Then, the Cramér-Rao bounds for Gaussian process based system models are derived and evaluated in an indoor positioning scenario.In addition, we estimate the positions of stationary devices by comparing the individual signal strength measurements with a pre-constructed fingerprinting database. The positioning accuracy is further compared to the case where a moving device is positioned using a time series of radio signal strength measurements.Moreover, Gaussian processes have been applied to sports analytics, where trajectory modeling for athletes is studied. The proposed framework can be further utilized to carry out, for instance, performance prediction and analysis, health condition monitoring, etc. Finally, a grey-box modeling is proposed to analyze the forces, particularly in cross-country skiing races, by combining a deterministic kinetic model with Gaussian process.
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| 10. |
- Zhao, Yuxin, 1986-, et al.
(författare)
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Sequential Monte Carlo Methods and Theoretical Bounds for Proximity Report Based Indoor Positioning
- 2018
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Ingår i: IEEE Transactions on Vehicular Technology. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9545 .- 1939-9359. ; 67:6, s. 5372-5386
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Tidskriftsartikel (refereegranskat)abstract
- The commercial interest in proximity services is increasing. Application examples include location-based information and advertisements, logistics, social networking, file sharing, etc. In this paper, we consider positioning of devices based on a time series of proximity reports from a mobile device to a network node. This corresponds to nonlinear measurements with respect to the device position in relation to the network nodes. Motion model will be needed together with the measurements to determine the position of the device. Therefore, sequential Monte Carlo methods, namely particle filtering and smoothing, are applicable for positioning. Positioning performance is evaluated in a typical office area with Bluetooth-low-energy beacons deployed for proximity detection and report, and is further compared to parametric Cramér-Rao lower bounds. Finally, the position accuracy is also evaluated with real experimental data.
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