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Register a new userModified CRB for Location and Velocity Estimation using Signals of Opportunity
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Added by
Mei Leng
Publication date
2013
fields
Informatics Engineering
and research's language is
English
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We consider the problem of localizing two sensors using signals of opportunity from beacons with known positions. Beacons and sensors have asynchronous local clocks or oscillators with unknown clock skews and offsets. We model clock skews as random, and analyze the biases introduced by clock asynchronism in the received signals. By deriving the equivalent Fisher information matrix for the modified Bayesian Cramer-Rao lower bound (CRLB) of sensor position and velocity estimation, we quantify the errors caused by clock asynchronism.
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Integrated satellite-terrestrial communications networks aim to exploit both the satellite and the ground mobile communications, thus providing genuine ubiquitous coverage. For 5G integrated low earth orbit (LEO) satellite communication systems, the timing advance (TA) is required to be estimated in the initial random access procedure in order to facilitate the uplink frame alignment among different users. However, due to the inherent characteristics of LEO satellite communication systems, e.g., wide beam coverage and long propagation delays, the existing 5G terrestrial uplink TA scheme is not applicable in the satellite networks. In this paper, we investigate location-based TA estimation for 5G integrated LEO satellite communication systems. We obtain the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements in the downlink timing and frequency synchronization phase, which are made from the satellite at different time instants. We propose to take these measurements for either UE geolocation or ephemeris estimation, thus calculating the TA value. The estimation is then formulated as a quadratic optimization problem whose globally optimal solution can be obtained by a quadratic penalty algorithm. To reduce the computational complexity, we further propose an alternative approximation method based on iteratively performing a linearization procedure on the quadratic equality constraints. Numerical results show that the proposed methods can approach the constrained Cramer-Rao lower bound (CRLB) of the TA estimation and thus assure uplink frame alignment for different users.
Visible Light Communication (VLC) using light emitting diodes (LEDs) has been gaining increasing attention in recent years as it is appealing for a wide range of applications such as indoor positioning. Orthogonal frequency division multiplexing (OFDM) has been applied to indoor wireless optical communications in order to mitigate the effect of multipath distortion of the optical channel as well as increasing data rate. In this paper, a novel OFDM VLC system is proposed which can be utilized for both communications and indoor positioning. A positioning algorithm based on power attenuation is used to estimate the receiver coordinates. We further calculate the positioning errors in all the locations of a room and compare them with those using single carrier modulation scheme, i.e., on-off keying (OOK) modulation. We demonstrate that OFDM positioning system outperforms its conventional counterpart. Finally, we investigate the impact of different system parameters on the positioning accuracy of the proposed OFDM VLC system.
In many sensing applications, typically radio signals are emitted by a radar and from the bounced reflections of the obstacles, inference about the environment is made. Even though radars can be used to sense the landscapes around the user-equipment (UE) such as whether UE is in the forested region, inside buildings, etc., it is not suitable in many wireless applications as many UEs does not have radars in them. Using radar will also increase the cost and power requirements on the UEs in applications requiring sensing of the landscapes. In this paper, we provide a mechanism where basestation (BS) is able to sense the UEs landscape without the use of a radar. We propose an artificial intelligence (AI) based approach with suitable choice of the features derived from the wireless channel to infer the landscape of the UEs. Results for the proposed methods when applied to practical environments such as London city scenario yields a precision score of more than 95 percent.
Future sub-THz cellular deployments may be utilized to complement the coverage of the global positioning system (GPS) and provide centimeter-level accuracy. In this work, we use measurement data at 142 GHz to test a map-based position location algorithm in an outdoor urban microcell (UMi) environment. We utilize an extended Kalman filter (EKF) to track the position of the user equipment (UE) along a rectangular track, with the transmitter-receiver separation distances varying from 24.3 m to 52.8 m. The position and velocity of the UE are tracked by the EKF, with measurements of the angle of arrival and time of flight information obtained along an outdoor track, to provide a mean accuracy of 24.8 cm at 142 GHz, over 34 UE locations, using a single base station in line-of-sight and non-line-of-sight.
We consider least squares estimators of carrier phase and amplitude from a noisy communications signal that contains both pilot signals, known to the receiver, and data signals, unknown to the receiver. We focus on signaling constellations that have symbols evenly distributed on the complex unit circle, i.e., M-ary phase shift keying. We show, under reasonably mild conditions on the distribution of the noise, that the least squares estimator of carrier phase is strongly consistent and asymptotically normally distributed. However, the amplitude estimator is not consistent, but converges to a positive real number that is a function of the true carrier amplitude, the noise distribution and the size of the constellation. Our theoretical results can also be applied to the case where no pilot symbols exist, i.e., noncoherent detection. The results of Monte Carlo simulations are provided and these agree with the theoretical results.
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