High-resolution multipath channel parameter estimation using wavelet analysis

This thesis explores the novel use of wavelet analysis as a high-resolution digital signal processing algorithm for multipath channel parameter estimation. The results obtained from this research indicate that this wavelet-based digital signal processing algorithm overcomes the resolution limitation in conventional high-resolution algorithm. This may provide a more cost-effective means of implementing channel sounding equipments for very high-resolution measurements

Detecting and locating electronic devices using their unintended electromagnetic emissions

Electronically-initiated explosives can have unintended electromagnetic emissions which propagate through walls and sealed containers. These emissions, if properly characterized, enable the prompt and accurate detection of explosive threats. The following dissertation develops and evaluates techniques for detecting and locating common electronic initiators. The unintended emissions of radio receivers and microcontrollers are analyzed. These emissions are low-power radio signals that result from the device\u27s normal operation. In the first section, it is demonstrated that arbitrary signals can be injected into a radio receiver\u27s unintended emissions using a relatively weak stimulation signal. This effect is called stimulated emissions. The performance of stimulated emissions is compared to passive detection techniques. The novel technique offers a 5 to 10 dB sensitivity improvement over passive methods for detecting radio receivers. The second section develops a radar-like technique for accurately locating radio receivers. The radar utilizes the stimulated emissions technique with wideband signals. A radar-like system is designed and implemented in hardware. Its accuracy tested in a noisy, multipath-rich, indoor environment. The proposed radar can locate superheterodyne radio receivers with a root mean square position error less than 5 meters when the SNR is 15 dB or above. In the third section, an analytic model is developed for the unintended emissions of microcontrollers. It is demonstrated that these emissions consist of a periodic train of impulses. Measurements of an 8051 microcontroller validate this model. The model is used to evaluate the noise performance of several existing algorithms. Results indicate that the pitch estimation techniques have a 4 dB sensitivity improvement over epoch folding algorithms --Abstract, page iii

Review of Techniques to enhance the Accuracy of GNSS Receiver

Multipath is one of the major error sources in satellite based navigation systems. Most of the satellite based navigation system works on the DS-CDMA techniques in L-band spectrum. The position of user is estimated based on the principle of Triangulation. Various position error occur in this techniques such as Dilution of Precision (DOP), Satellite and Clock error, Ephemeris error, Ionospheric error, Tropospheric error and Multipath error. All these errors have been discussed briefly. There are two major errors: Ionospheric and Multipath errors. Normally Ionospheric errors can be mitigated using Dual frequency transmission or using a suitable algorithm. Multipath error can be mitigated using various techniques such as Multipath Estimating Delay Lock Loop (MEDLL), Modified RAKE Delay Lock Loop (MRDLL), Multipath Mitigation Technology (MMT), Narrow Correlator, Double Delta technique Vision Correlator (VC), TurboDLL and others. These techniques have been discussed in detail in this paper. The technique using the Rake receiver is generally used in Communication System. It is envesaged that this technique to mitigate the multipath error significantly

FAA/NASA Joint University Program for Air Transportation Research, 1992-1993

The research conducted during the academic year 1992-1993 under the FAA/NASA sponsored Joint University Program for Air Transportation Research is summarized. The year end review was held at Ohio University, Athens, Ohio, 17-18 June 1993. The Joint University Program is a coordinated set of three grants sponsored by the Federal Aviation Administration and NASA Langley Research Center, one each with the Massachusetts Institute of Technology, Ohio University, and Princeton University. Completed works, status reports, and annotated bibliographies are presented for research topics, which include navigation, guidance, and control theory and practice, aircraft performance, human factors and air traffic management. An overview of the year's activities for each university is also presented

Stochastic Modeling and Estimation of Wireless Channels with Application to Ultra Wide Band Systems

This thesis is concerned with modeling of both space and time variations of Ultra Wide Band (UWB) indoor channels. The most common empirically determined amplitude distribution in many UWB environments is Nakagami distribution. The latter is generalized to stochastic diffusion processes which capture the dynamics of UWB channels. In contrast with the traditional models, the statistics of the proposed models are shown to be time varying, but converge in steady state to their static counterparts. System identification algorithms are used to extract various channel parameters using received signal measurement data, which are usually available at the receiver. The expectation maximization (EM) algorithm and the Kalman filter (KF) are employed in estimating channel parameters as well as the inphase and quadrature components, respectively. The proposed algorithms are recursive and therefore can be implemented in real time. Further, sufficient conditions for the convergence of the EM algorithm are provided. Comparison with recursive Least-square (LS) algorithms is carried out using experimental measurements. Distributed stochastic power control algorithms based on the fixed point theorem and stochastic approximations are used to solve for the optimal transmit power problem and numerical results are also presented. A framework which can capture the statistics of the overall received signal and a methodology to estimate parameters of the counting process based on the received signal is developed. Furthermore, second moment statistics and characteristic functions are computed explicitly and considered as an extension of Rice’s shot noise analysis. Another two important components, input design and model selection are also considered. Gel’fand n-widths and Time n-widths are used to represent the inherent error introduced by input design. Kolmogorov n-width is used to characterize the representation error introduced by model selection. In particular, it is shown that the optimal model for reducing the representation error is a finite impulse response (FIR) model and the optimal input is an impulse at the start of the observation interval

GPS Stochastic Modelling - Signal Quality Measures and ARMA Processes

This work extends the GPS stochastic model using SNR measurements and time series analysis of observation residuals. The proposed SNR-based observation weighting model significantly improves the results of GPS data analysis, while the temporal correlation of GPS observation noise can be efficiently described by means of ARMA processes. Furthermore, this work includes an up-to-date overview of the GPS error effects and a comprehensive description of various mathematical methods

Characterization of Single- and Multi-antenna Wireless Channels

The wireless propagation channel significantly influences the received signal, so that it needs to be modeled effectively. Extensive measurements and analysis are required for investigating the validity of theoretical models and postulating new models based on measurements. Such measurements, analysis, and modeling are the topic of this thesis. The focus of the included contributions are Multiple-Input Multiple-Output (MIMO) propagation channels and radio channels for sensor network applications. Paper I presents results from one of the first MIMO measurements for a double-directional characterization of the outdoor-to-indoor wireless propagation channel. Such channels are of interest for both cellular and wireless LAN applications. We discuss physical aspects of building penetration, and also provide statistics of angle and delay spreads in the channel. The paper also investigates the coupling between DOD and DOA and the two spectra are found to have non-negligible dependence. We test the applicability of three analytical channel models that make different assumptions on the coupling between DODs and DOAs. Our results indicate that analytical models, that impose fewer restrictions on the DOD to DOA coupling, should be used preferrably over models such as the Kronecker model that have more restrictive assumptions. Paper II presents a cluster-based analysis of the outdoor-to-indoor MIMO measurements analyzed in Paper I. A subset of parameters of the COST 273 channel model, a generic model for MIMO propagation channels, are characterized for the outdoor-to-indoor scenario. MPC parameters are extracted at each measured location using a high-resolution algorithm and clusters of MPCs are identified with an automated clustering approach. In particular, the adopted clustering approach requires that all MPC parameters must be similar in order for the MPCs to form a cluster. A statistical analysis of the identified clusters is performed for both the intra- and inter-cluster properties. Paper III analyzes the spatial fading distribution for a range of canonical sensor deployment scenarios. The presented results are relevant to communicating within, and between, clusters of nodes. Contrary to the widely accepted assumption in published literature that the channel is AWGN at a small-enough distance, our measurements indicate that values of the Rice factor do not, in general, increase monotonically as the Tx-Rx distance is reduced. A probability mixture model is presented, with distance dependent parameters, to account for the distance dependent variations of the Rice factor. A simulation model that includes small- and large-scale fading effects is presented. According to the modeling approach, a sensor node placed anywhere within the spatial extent of a small-scale region will experience the channel statistics applicable to that region. Paper IV presents results characterizing a radio channel for outdoor short-range sensor networks. A number of antennas are placed on the ground in an open area and time-variation of the channel is induced by a person moving in the vicinity of the nodes. The channel statistics of both the LOS path and the overall narrowband signal are non-stationary. We investigate the stationarity interval length to be used for small-scale analysis. Our analysis of the various measured links shows that the Rx signal strength is significantly influenced by a moving person only when the person blocks the LOS path. We present a generic approach for modeling the LOS blockage, and also model the time-variant Doppler spectrum of the channel's scattered components