Brandon Merkl

Investigation of High-Accuracy Indoor 3-D Positioning Using UWB Technology

There are many challenges in building an ultra-wideband (UWB) indoor local positioning system for high-accuracy applications. These challenges include reduced accuracy due to multipath interference, sampling rate limitations, tag synchronization, and antenna phase-center variation. Each of these factors must be addressed to achieve millimeter or sub-millimeter accuracy. The developed system architecture is presented where a 300-ps Gaussian pulse modulates an 8-GHz carrier signal and is transmitted through an omni-directional UWB antenna. Receiver-side peak detection, a low-cost subsequential-sampling mixer utilizing a direct digital synthesizer, high fidelity 10-MHz crystals, and Vivaldi phase-center calibration are utilized to mitigate these challenging problems. Synchronized and unsynchronized experimental results validated with a sub-millimeter accurate optical tracking system are presented with a detailed discussion of various system errors.

Real-Time Noncoherent UWB Positioning Radar With Millimeter Range Accuracy: Theory and Experiment

In this paper, we propose a novel architecture for ultra-wideband (UWB) positioning systems, which combines the architectures of carrier-based UWB systems and traditional energy detection-based UWB systems. By implementing the novel architecture, we have successfully developed a standalone noncoherent system for positioning both static and dynamic targets in an indoor environment with approximately 2 and 5 mm of 3-D accuracy, respectively. The results are considered a great milestone in developing such technology. 1-D and 3-D experiments have been carried out and validated using an optical reference system, which provides better than 0.3-mm 3-D accuracy. This type of indoor high-accuracy wireless localization system has many unique applications including robot control, surgical navigation, sensitive material monitoring, and asset tracking.

Automatic methods for characterization of sexual dimorphism of adult femora: distal femur

Quantifying sex differences in femoral size and shape has extensive applications in forensics and prosthesis design. By applying strong statistical techniques such as principal component analysis (PCA), certain three-dimensional (3D) morphological variations of adult femora can be quantified over various femoral sizes. Coupling this statistical approach with a novel feature generation and extraction technique, localization of statistically significant (p < 0.05) features are automatically defined and measured. Also, predefined anatomical landmarks and surgical axes have been calculated automatically. In all methods, femoral scale is controlled as a possible parameter of shape. By extensively comparing measurements across 92 male and 74 female femora, the dimorphic characteristics of the distal femur are shown. These differences have not been accounted for in many prosthetic systems and consequently these systems have limited sizing accuracy.

Development of an UWB Indoor 3D Positioning Radar with Millimeter Accuracy

A high resolution ultra wideband (UWB) positioning radar system based on time difference of arrival (TDOA) has been developed. The UWB radar system provides millimeter accuracy in dense multipath indoor environments for 1D, 2D, and 3D localization. The system is fully compliant with the FCC UWB regulations and utilizes time domain measurements to suppress both multipath signals and non-line of sight (NLOS) errors and has a potential for even sub-mm accuracy

High accuracy UWB localization in dense indoor environments

UWB communication and localization systems have many inherent advantages for robust performance in dense, indoor multipath environments. Although UWB systems have been designed for numerous industrial applications, there exists the need for short range (i.e. 5-10 m) UWB localization systems with accuracy an order of magnitude higher (i.e. mm-range) than existing commercial systems. Many system level challenges must be overcome to achieve accuracy on the order of tens of picoseconds, such as high Rx sampling rate, Tx-Rx LO phase noise, Tx-Rx pulse repetition frequency clock phase noise, Rx-induced jitter from sequential sampling, Rx-side calibration of phase offsets in I and Q channels, multipath interference due to dense indoor environments, etc. A detailed system level simulation is setup in order to quantify the contribution of these effects on overall system accuracy. Simulation results are used to highlight these system level errors and show how they can be mitigated.

A System-Level Simulation Framework for UWB Localization

In this paper we present a comprehensive simulation framework that can accurately simulate our indoor UWB positioning system including the analog front-ends, digital back-ends, and channel effects. Experimental results from our UWB positioning system are compared to simulated results to validate the accuracy of the simulation framework. Simulated results illustrate the design decisions made in optimizing overall system performance. Multiple peak detection algorithms are presented, and the robustness of our leading-edge detection algorithm is shown even in dense multipath environments. Geometric effects are examined by simulating various base station configurations. This comprehensive simulation framework provides an in-depth analysis of our UWB positioning system and also provides a general framework for rapid prototyping and design of complex wireless systems.

3D Statistical Shape Models of Patella for Sex Classification

This paper proposes a new sex classification method from patellae using a novel automated feature extraction technique. A dataset of 228 patellae (95 females and 133 males) was collected and CT scanned. After the CT data was segmented, a set of features was automatically extracted, normalized, and ranked. These features include geometric features, moments, principal axes, and principal components. A feature vector of 45 dimensions for each subject was then constructed. A set of statistical and supervised neural network classification methods were used to classify the patellar feature vectors according to sex. Different classification methods were compared. Classification success ranged from 83.77% average classification rate with labeling using fuzzy C-means method (FCM), to 90.3% for linear discriminant function (LDF) analysis. We obtained results of 96.02% and 93.51% training and testing classification rates (respectively) using feedforward backpropagation neural networks (NN). These promising results encourage the usage of this method in forensic anthropology for identifying the sex from incomplete skeletons containing at least one patella

Base station orientation calibration in 3-D indoor UWB positioning

A method is proposed to correct three-dimensional (3D) positioning error due to base station antenna orientation that takes into account non-boresight electrical length differences due to antenna phase center errors. An automated algorithm is used to calibrate an ultra-wideband (UWB) system using only a starting estimate of the base station position and acquired positions central to the base stations. The true positions of the acquired 3D calibration points are unknown to the calibration algorithm. Upon completion of the algorithm, the base station orientation is estimated, along with estimates of electrical length offsets due to potential cable length differences. This method is designed to minimize small errors due to base station position and orientation uncertainty. The algorithm is shown to be robust given the availability of accurate 1D ranging can be provided by the system.