arXiv subjects

Peter Händel

Publications and source records attributed to Peter Händel.

27 records · Page 2Linked to original sources

arXiv2015

Phase-Noise Mitigation in OFDM by Best Match Trajectories

This paper proposes a novel approach to phase-noise compensation. The basic idea is to approximate the phase-noise statistics by a finite number of realizations, i.e., a phase-noise codebook. The receiver then uses an augmented received signal model, where the codebook index is estimated along with other parameters. The realization of the basic idea depends on the details of the air interface, the phase-noise statistics, the propagation scenario and the computational constraints. In this paper, we will focus on a MQAM-OFDM system with pilot sub-carriers within each OFDM symbol. The channel is frequency selective, fading and unknown. A decision-feedback method is employed to further enhance performance of the system. Simulation results are shown for uncoded and coded systems to illustrate the performance of the algorithm, which is also compared with previously employed methods. Our simulations show that for a 16-QAM coded OFDM system over a frequency selective Rayleigh fading channel affected by phase noise with root-mean-square (RMS) of 14.4 degrees per OFDM symbol, the proposed algorithm is 1.5dB from the ideal phase-noise free case at a BER of $10^{-4}$. The performance of the best reference scheme is 2.5dB from the ideal case at BER of $10^{-4}$. The proposed scheme is also computationally attractive.

cs.IT↗

arXiv2015

Joint Ranging and Clock Parameter Estimation by Wireless Round Trip Time Measurements

In this paper we develop a new technique for estimating fine clock errors and range between two nodes simultaneously by two-way time-of-arrival measurements us- ing impulse-radio ultra-wideband signals. Estimators for clock parameters and the range are proposed that are robust with respect to outliers. They are analyzed numerically and by means of experimental measurement campaigns. The technique and derived estimators achieve accuracies below 1Hz for frequency estimation, below 1 ns for phase estimation and 20 cm for range estimation, at 4m distance using 100MHz clocks at both nodes. Therefore, we show that the proposed joint approach is practical and can simultaneously provide clock synchronization and positioning in an experimental system.

cs.NI↗

arXiv2015

Ranging without time stamps exchanging

We investigate the range estimate between two wireless nodes without time stamps exchanging. Considering practical aspects of oscillator clocks, we propose a new model for ranging in which the measurement errors include the sum of two distributions, namely, uniform and Gaussian. We then derive an approximate maximum likelihood estimator (AMLE), which poses a difficult global optimization problem. To avoid the difficulty in solving the complex AMLE, we propose a simple estimator based on the method of moments. Numerical results show a promising performance for the proposed technique.

stat.AP↗

arXiv2015

Multi Detector Fusion of Dynamic TOA Estimation using Kalman Filter

In this paper, we propose fusion of dynamic TOA (time of arrival) from multiple non-coherent detectors like energy detectors operating at sub-Nyquist rate through Kalman filtering. We also show that by using multiple of these energy detectors, we can achieve the performance of a digital matched filter implementation in the AWGN (additive white Gaussian noise) setting. We derive analytical expression for number of energy detectors needed to achieve the matched filter performance. We demonstrate in simulation the validity of our analytical approach. Results indicate that number of energy detectors needed will be high at low SNRs and converge to a constant number as the SNR increases. We also study the performance of the strategy proposed using IEEE 802.15.4a CM1 channel model and show in simulation that two sub-Nyquist detectors are sufficient to match the performance of digital matched filter.

cs.IT↗

arXiv2013

Cooperative localization by dual foot-mounted inertial sensors and inter-agent ranging

The implementation challenges of cooperative localization by dual foot-mounted inertial sensors and inter-agent ranging are discussed and work on the subject is reviewed. System architecture and sensor fusion are identified as key challenges. A partially decentralized system architecture based on step-wise inertial navigation and step-wise dead reckoning is presented. This architecture is argued to reduce the computational cost and required communication bandwidth by around two orders of magnitude while only giving negligible information loss in comparison with a naive centralized implementation. This makes a joint global state estimation feasible for up to a platoon-sized group of agents. Furthermore, robust and low-cost sensor fusion for the considered setup, based on state space transformation and marginalization, is presented. The transformation and marginalization are used to give the necessary flexibility for presented sampling based updates for the inter-agent ranging and ranging free fusion of the two feet of an individual agent. Finally, characteristics of the suggested implementation are demonstrated with simulations and a real-time system implementation.

cs.RO↗

arXiv2013

Timing estimation in distributed sensor and control systems with central processing

We consider the problem of estimating timing of measurements and actuation in distributed sensor and control systems with central processing. The focus is on direct timing estimation for scenarios where clock synchronization is not feasible or desirable. Models of the timing and central and peripheral time stamps are motivated and derived from underlying clock and communication delay definitions and models. Heuristics for constructing a system time is presented and it is outlined how the joint timing and the plant state estimation can be handled. For a simple set of underlying clock and communication delay models, inclusion of peripheral unit time stamps is shown to reduce jitter, and it is argued that in general it will give significant jitter reduction. Finally, a numerical example is given of a contemporary system design.

eess.SY↗

arXiv2013

Recursive Bayesian Initialization of Localization Based on Ranging and Dead Reckoning

The initialization of the state estimation in a localization scenario based on ranging and dead reckoning is studied. Specifically, we start with a cooperative localization setup and consider the problem of recursively arriving at a uni-modal state estimate with sufficiently low covariance such that covariance based filters can be used to estimate an agent's state subsequently. A number of simplifications/assumptions are made such that the estimation problem can be seen as that of estimating the initial agent state given a deterministic surrounding and dead reckoning. This problem is solved by means of a particle filter and it is described how continual states and covariance estimates are derived from the solution. Finally, simulations are used to illustrate the characteristics of the method and experimental data are briefly presented.

cs.RO↗

arXiv2013

Self-Localization of Asynchronous Wireless Nodes With Parameter Uncertainties

We investigate a wireless network localization scenario in which the need for synchronized nodes is avoided. It consists of a set of fixed anchor nodes transmitting according to a given sequence and a self-localizing receiver node. The setup can accommodate additional nodes with unknown positions participating in the sequence. We propose a localization method which is robust with respect to uncertainty of the anchor positions and other system parameters. Further, we investigate the Cramér-Rao bound for the considered problem and show through numerical simulations that the proposed method attains the bound.

math.ST↗

arXiv2012

Bayesian Estimation with Distance Bounds

We consider the problem of estimating a random state vector when there is information about the maximum distances between its subvectors. The estimation problem is posed in a Bayesian framework in which the minimum mean square error (MMSE) estimate of the state is given by the conditional mean. Since finding the conditional mean requires multidimensional integration, an approximate MMSE estimator is proposed. The performance of the proposed estimator is evaluated in a positioning problem. Finally, the application of the estimator in inequality constrained recursive filtering is illustrated by applying the estimator to a dead-reckoning problem. The MSE of the estimator is compared with two related posterior Cramér-Rao bounds.

math.ST↗