An Implementation Approach and Performance Analysis of Image Sensor Based Multilateral Indoor Localization and Navigation System

Optical camera communication (OCC) exhibits considerable importance nowadays in various indoor camera based services such as smart home and robot-based automation. An android smart phone camera that is mounted on a mobile robot (MR) offers a uniform communication distance when the camera remains at the same level that can reduce the communication error rate. Indoor mobile robot navigation (MRN) is considered to be a promising OCC application in which the white light emitting diodes (LEDs) and an MR camera are used as transmitters and receiver respectively. Positioning is a key issue in MRN systems in terms of accuracy, data rate, and distance. We propose an indoor navigation and positioning combined algorithm and further evaluate its performance. An android application is developed to support data acquisition from multiple simultaneous transmitter links. Experimentally, we received data from four links which are required to ensure a higher positioning accuracy

Optimal Precoders for Tracking the AoD and AoA of a mm-Wave Path

In millimeter-wave channels, most of the received energy is carried by a few paths. Traditional precoders sweep the angle-of-departure (AoD) and angle-of-arrival (AoA) space with directional precoders to identify directions with largest power. Such precoders are heuristic and lead to sub-optimal AoD/AoA estimation. We derive optimal precoders, minimizing the Cram\'{e}r-Rao bound (CRB) of the AoD/AoA, assuming a fully digital architecture at the transmitter and spatial filtering of a single path. The precoders are found by solving a suitable convex optimization problem. We demonstrate that the accuracy can be improved by at least a factor of two over traditional precoders, and show that there is an optimal number of distinct precoders beyond which the CRB does not improve.Comment: Resubmission to IEEE Trans. on Signal Processing. 12 pages and 9 figure

Mitigation of GPS Multipath Using Polarization and Spatial Diversities

This paper presents a GPS multipath mitigation method using a dual circularly polarized antenna array and a multi-channel receiver. The method is based on the exploitation of both polarization and spatial diversity associated with a GPS signal and its multipath signals available at the receiver input. Conventional GPS antennas are right-hand circularly polarized (RHCP) to suppress multipath contributions to the input. This polarization-based discrimination of multipath signal cannot completely eliminate multipath induced GPS range measurement errors. We present an algorithm that performs spatial processing on the input from the left-hand circular polarized (LHCP) array with an increased relative strength of the multipath signal, thereby providing improved multipath angle of arrival (AOA) estimation. With the known multipath AOA and direct signal AOA (which can be obtained from almanac/ephemeris together with the antenna attitude or estimated in a separate process), we can then take advantage of the spatial diversity of the direct signal and multipath by applying null-steering to the RHCP array input. The paper presents the algorithm and simulation results for a uniform linear array receiving one direct signal and one multipath. Our preliminary studies showed that the multipath AOA estimator produces negligible error if the direct signal and multipath AOA are not close to each other (more than 5 degrees apart) and that the direct signal is not at low elevation. The results also suggested that longer time delay between the direct and multipath signal will increase multipath AOA estimation error but this increase is tolerable. Furthermore, we demonstrated that the multipath estimation improves with increasing spatial diversity for multipath and direct GPS signals even if the signal arrivals are close in time. Finally, we demonstrated that the multipath mitigation technique does produce an improved receiver correlator function which directly impacts the GPS code range measurement accurac

An indoor variance-based localization technique utilizing the UWB estimation of geometrical propagation parameters

A novel localization framework is presented based on ultra-wideband (UWB) channel sounding, employing a triangulation method using the geometrical properties of propagation paths, such as time delay of arrival, angle of departure, angle of arrival, and their estimated variances. In order to extract these parameters from the UWB sounding data, an extension to the high-resolution RiMAX algorithm was developed, facilitating the analysis of these frequency-dependent multipath parameters. This framework was then tested by performing indoor measurements with a vector network analyzer and virtual antenna arrays. The estimated means and variances of these geometrical parameters were utilized to generate multiple sample sets of input values for our localization framework. Next to that, we consider the existence of multiple possible target locations, which were subsequently clustered using a Kim-Parks algorithm, resulting in a more robust estimation of each target node. Measurements reveal that our newly proposed technique achieves an average accuracy of 0.26, 0.28, and 0.90 m in line-of-sight (LoS), obstructed-LoS, and non-LoS scenarios, respectively, and this with only one single beacon node. Moreover, utilizing the estimated variances of the multipath parameters proved to enhance the location estimation significantly compared to only utilizing their estimated mean values

5G Positioning and Mapping with Diffuse Multipath

5G mmWave communication is useful for positioning due to the geometric connection between the propagation channel and the propagation environment. Channel estimation methods can exploit the resulting sparsity to estimate parameters(delay and angles) of each propagation path, which in turn can be exploited for positioning and mapping. When paths exhibit significant spread in either angle or delay, these methods breakdown or lead to significant biases. We present a novel tensor-based method for channel estimation that allows estimation of mmWave channel parameters in a non-parametric form. The method is able to accurately estimate the channel, even in the absence of a specular component. This in turn enables positioning and mapping using only diffuse multipath. Simulation results are provided to demonstrate the efficacy of the proposed approach