Least-square based recursive optimization for distance-based source localization

In this paper we study the problem of driving an agent to an unknown source whose location is estimated in real-time by a recursive optimization algorithm. The optimization criterion is subject to a least-square cost function constructed from the distance measurements to the target combined with the agent's self-odometry. In this work, two important issues concerning real world application are directly addressed, which is a discrete-time recursive algorithm for concurrent control and estimation, and consideration for input saturation. It is proven that with proper choices of the system's parameters, stability of all system states, including on-board estimator variables and the agent-target relative position can be achieved. The convergence of the agent's position to the target is also investigated via numerical simulation

Adaptive Wireless Biomedical Capsule Localization and Tracking

Wireless capsule endoscopy systems have been shown as a gold step to develop future wireless biomedical multitask robotic capsules, which will be utilized in micro surgery, drug delivery, biopsy and multitasks of the endoscopy. In such wireless capsule endoscopy systems, one of the most challenging problems is accurate localization and tracking of the capsule inside the human body. In this thesis, we focus on robotic biomedical capsule localization and tracking using range measurements via electromagetic wave and magnetic strength based sensors. First, a literature review of existing localization techniques with their merits and limitations is presented. Then, a novel geometric environmental coefficient estimation technique is introduced for time of flight (TOF) and received signal strength (RSS) based range measurement. Utilizing the proposed environmental coefficient estimation technique, a 3D wireless biomedical capsule localization and tracking scheme is designed based on a discrete adaptive recursive least square algorithm with forgetting factor. The comparison between localization with novel coefficient estimation technique and localization with known coefficient is provided to demonstrate the proposed technique’s efficiency. Later, as an alternative to TOF and RSS based sensors, use of magnetic strength based sensors is considered. We analyze and demonstrate the performance of the proposed techniques and designs in various scenarios simulated in Matlab/Simulink environment

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

Through-the-Wall Imaging and Multipath Exploitation

We consider the problem of using electromagnetic sensing to estimate targets in complex environments, such as when they are hidden behind walls and other opaque objects. The often unknown electromagnetic interactions between the target and the surrounding area, make the problem challenging. To improve our results, we exploit information in the multipath of the objects surrounding both the target and the sensors. First, we estimate building layouts by using the jump-diffusion algorithm and employing prior knowledge about typical building layouts. We also take advantage of a detailed physical model that captures the scattering by the inner walls and efficiently utilizes the frequency bandwidth. We then localize targets hidden behind reinforced concrete walls. The sensing signals reflected from the targets are significantly distorted and attenuated by the embedded metal bars. Using the surface formulation of the method of moments, we model the response of the reinforced walls, and incorporate their transmission coefficients into the beamforming method to achieve better estimation accuracy. In a related effort, we utilize the sparsity constraint to improve electromagnetic imaging of hidden conducting targets, assuming that a set of equivalent sources can be substituted for the targets. We derive a linear measurement model and employ l1 regularization to identify the equivalent sources in the vicinity of the target surfaces. The proposed inverse method reconstructs the target shape in one or two steps, using single-frequency data. Our results are experimentally verified. Finally, we exploit the multipath from sensor-array platforms to facilitate direction finding. This in contrast to the usual approach, which utilizes the scattering close to the targets. We analyze the effect of the multipath in a statistical signal processing framework, and compute the Cramer-Rao bound to obtain the system resolution. We conduct experiments on a simple array platform to support our theoretical approach

Use of a 3-D Wireless Power Transfer Technique as a Method for Capsule Localization

Capsule endoscopy has been heralded as a technological milestone in the diagnosis and therapeutics of gastrointestinal (GI) pathologies. The location and position of the capsule within the GI tract are important information for subsequent surgical intervention or local drug delivery. Accurate information of capsule location is therefore required during endoscopy. Although radio frequency (RF)-based, magnetic tracking and video localization have been investigated in the past, the complexity of those systems and potential inaccuracy in the localization data necessitate the scope for further research. This article proposes the dual use of a wireless power transfer (WPT) configuration as a method to enable the determination of the location of an endoscopic capsule. Measurements conducted on a homogeneous agar-based liquid phantom predict a maximum error of 12% between the calculated and measured trajectories of the capsule in a working volume of 100 mm $\times 100$ mm $\times 100$ mm

A Survey on Subsurface Signal Propagation

Wireless Underground Communication (WUC) is an emerging field that is being developed continuously. It provides secure mechanism of deploying nodes underground which shields them from any outside temperament or harsh weather conditions. This paper works towards introducing WUC and give a detail overview of WUC. It discusses system architecture of WUC along with the anatomy of the underground sensor motes deployed in WUC systems. It also compares Over-the-Air and Underground and highlights the major differences between the both type of channels. Since, UG communication is an evolving field, this paper also presents the evolution of the field along with the components and example UG wireless communication systems. Finally, the current research challenges of the system are presented for further improvement of the WUCs