Performance Limits and Geometric Properties of Array Localization

Location-aware networks are of great importance and interest in both civil and military applications. This paper determines the localization accuracy of an agent, which is equipped with an antenna array and localizes itself using wireless measurements with anchor nodes, in a far-field environment. In view of the Cram\'er-Rao bound, we first derive the localization information for static scenarios and demonstrate that such information is a weighed sum of Fisher information matrices from each anchor-antenna measurement pair. Each matrix can be further decomposed into two parts: a distance part with intensity proportional to the squared baseband effective bandwidth of the transmitted signal and a direction part with intensity associated with the normalized anchor-antenna visual angle. Moreover, in dynamic scenarios, we show that the Doppler shift contributes additional direction information, with intensity determined by the agent velocity and the root mean squared time duration of the transmitted signal. In addition, two measures are proposed to evaluate the localization performance of wireless networks with different anchor-agent and array-antenna geometries, and both formulae and simulations are provided for typical anchor deployments and antenna arrays.Comment: to appear in IEEE Transactions on Information Theor

Wireless capsule gastrointestinal endoscopy: direction of arrival estimation based localization survey

One of the significant challenges in Capsule Endoscopy (CE) is to precisely determine the pathologies location. The localization process is primarily estimated using the received signal strength from sensors in the capsule system through its movement in the gastrointestinal (GI) tract. Consequently, the wireless capsule endoscope (WCE) system requires improvement to handle the lack of the capsule instantaneous localization information and to solve the relatively low transmission data rate challenges. Furthermore, the association between the capsule’s transmitter position, capsule location, signal reduction and the capsule direction should be assessed. These measurements deliver significant information for the instantaneous capsule localization systems based on TOA (time of arrival) approach, PDOA (phase difference of arrival), RSS (received signal strength), electromagnetic, DOA (direction of arrival) and video tracking approaches are developed to locate the WCE precisely. The current article introduces the acquisition concept of the GI medical images using the endoscopy with a comprehensive description of the endoscopy system components. Capsule localization and tracking are considered to be the most important features of the WCE system, thus the current article emphasizes the most common localization systems generally, highlighting the DOA-based localization systems and discusses the required significant research challenges to be addressed

Single Platform Geolocation of Radio Frequency Emitters

The focus of this research is on single platform geolocation methods where the position of a single stationary radio frequency emitter is estimated from multiple simulated angle and frequency of arrival measurements taken from a single moving receiver platform. The analysis scenario considered consists of a single 6U CubeSat in low earth orbit receiving radio frequency signals from a stationary emitter located on the surface of the Earth. A multiple element receive antenna array and the multiple signal classification algorithm are used to estimate the angles of arrival of an impinging signal. The maximum likelihood estimator is used to estimate the frequency of arrival of the received signal. Four geolocation algorithms are developed and the accuracy performance is compared to the Cramer-Rao lower bounds through Monte Carlo simulations. Results from a system parameter sensitivity analysis show the combined angle and frequency of arrival geolocation maximum likelihood estimator consistently outperforms the other three geolocation algorithms

Crossed-dipole arrays for asynchronous DS-CDMA systems

Published versio

Radio Frequency Emitter Geolocation Using Cubesats

The ability to locate an RF transmitter is a topic of growing interest for civilian and military users alike. Geolocation can provide critical information for the intelligence community, search and rescue operators, and the warfighter. The technology required for geolocation has steadily improved over the past several decades, allowing better performance at longer baseline distances between transmitter and receiver. The expansion of geolocation missions from aircraft to spacecraft has necessitated research into how emerging geolocation methods perform as baseline distances are increased beyond what was previously considered. The CubeSat architecture is a relatively new satellite form which could enable small-scale, low-cost solutions to USAF geolocation needs. This research proposes to use CubeSats as a vehicle to perform geolocation missions in the space domain. The CubeSat form factor considered is a 6-unit architecture that allows for 6000 cm3 of space for hardware. There are a number of methods which have been developed for geolocation applications. This research compares four methods with various sensor configurations and signal properties. The four methods\u27 performance are assessed by simulating and modeling the environment, signals, and geolocation algorithms using MATLAB. The simulations created and run in this research show that the angle of arrival method outperforms the instantaneous received frequency method, especially at higher SNR values. These two methods are possible for single and dual satellite architectures. When three or more satellites are available, the direct position determination method outperforms the three other considered methods

mmWave V2V Localization in MU-MIMO Hybrid Beamforming

Recent trends for vehicular localization in millimetre-wave (mmWave) channels include employing a combination of parameters such as angle of arrival (AOA), angle of departure (AOD), and time of arrival (TOA) of the transmitted/received signals. These parameters are challenging to estimate, which along with the scattering and random nature of mmWave channels, and vehicle mobility lead to errors in localization. To circumvent these challenges, this paper proposes mmWave vehicular localization employing difference of arrival for time and frequency, with multiuser (MU) multiple-input-multiple-output (MIMO) hybrid beamforming; rather than relying on AOD/AOA/TOA estimates. The vehicular localization can exploit the number of vehicles present, as an increase in a number of vehicles reduces the Cramr-Rao bound (CRB) of error estimation. At 10 dB signal-to-noise ratio (SNR) both spatial multiplexing and beamforming result in comparable localization errors. At lower SNR values, spatial multiplexing leads to larger errors compared to beamforming due to formation of spurious peaks in the cross ambiguity function. Accuracy of the estimated parameters is improved by employing an extended Kalman filter leading to a root mean square (RMS) localization error of approximately 6.3 meters

MmWave V2V Localization in MU-MIMO Hybrid Beamforming

Recent trends for vehicular localization in millimetre-wave (mmWave) channels include employing a combination of parameters such as angle of arrival (AOA), angle of departure (AOD), and time of arrival (TOA) of the transmitted/received signals. These parameters are challenging to estimate, which along with the scattering and random nature of mmWave channels, and vehicle mobility lead to errors in localization. To circumvent these challenges, this paper proposes mmWave vehicular localization employing difference of arrival for time and frequency, with multiuser (MU) multiple-input-multiple-output (MIMO) hybrid beamforming; rather than relying on AOD/AOA/TOA estimates. The vehicular localization can exploit the number of vehicles present, as an increase in a number of vehicles reduces the Cramr-Rao bound (CRB) of error estimation. At 10 dB signal-to-noise ratio (SNR) both spatial multiplexing and beamforming result in comparable localization errors. At lower SNR values, spatial multiplexing leads to larger errors compared to beamforming due to formation of spurious peaks in the cross ambiguity function. Accuracy of the estimated parameters is improved by employing an extended Kalman filter leading to a root mean square (RMS) localization error of approximately 6.3 meters

Direction Finding With Mutually Orthogonal Antennas

Estimating the direction-of-arrival of incident electromagnetic plane waves (a.k.a. direction finding or DF) has typically been accomplished in the past using arrays of spatially separated antennas. The spatial separation produces a delay in each antenna\u27s measured voltage due to the finite propagation time as the wave strikes each antenna in succession. In this thesis, we approach the problem differently by using three antennas that have been oriented in orthogonal directions but are co-located at the origin of a coordinate system. Being co-located, this mutually orthogonal arrangement of antennas cannot detect the propagation phase delay and must rely solely on the polarization properties of the incident waves. Using the vector effective height concept, three algorithms are formulated. The first algorithm estimates the direction-of-arrival by computing a vector that is perpendicular to the locus of the instantaneous electric field vector. The second and third algorithms are based on the well-known maximum likelihood and MUSIC algorithms. Simulation results show that each algorithm can estimate the direction-of-arrival with a root-mean-squared error within 1° or less when the incident wave is circularly polarized, the antennas are small compared to wavelength, and the signal-to-noise ratio is above 20dB