Evaluating the Navigation Potential of the National Television System Committee Broadcast Signal

The accuracy and worldwide availability of the Global Positioning System (GPS) make it the dominant system for navigation and precise positioning. Unfortunately, many situations arise in which GPS may not be adequate, e.g., urban navigation. This research evaluates the navigation potential of the National Television System Committee (NTSC) broadcast signal using a time-difference-of-arrival (TDOA) algorithm. TDOA measurements are made using NTSC broadcast signals collected from low and high multipath environments. These measurements are then used to evaluate the severity and dynamic effects of NTSC broadcast multipath signals. Three data reduction algorithms were developed--one that modifies the classical cross-correlation TDOA approach, and two that difference the signals\u27 time-of-arrival at each receiver. Each algorithm was evaluated for consistency and accuracy in each environment. Multipath mitigation was demonstrated using a locally fabricated antenna. Collected NTSC broadcast signal samples reveal TDOA measurement errors ranging from 1 to 200 meters, with typical errors between 10 and 40 meters. Multipath was shown to be the dominant error source. However, errors due to the particular hardware configuration used in this research were also significant. Simple multipath mitigation techniques were able to reduce these errors, and analyses of the received waveforms provide the foundation for developing additional active multipath mitigation techniques. Simulations using eight television station locations near Dayton, Ohio reveal 40 meter position accuracy with the typical range errors found in this research. Extreme measurement errors from high multipath areas reduced this accuracy to 100 meters

A Linear Subspace Approach to Burst Communication Signal Processing

This dissertation focuses on the topic of burst signal communications in a high interference environment. It derives new signal processing algorithms from a mathematical linear subspace approach instead of the common stationary or cyclostationary approach. The research developed new algorithms that have well-known optimality criteria associated with them. The investigation demonstrated a unique class of multisensor filters having a lower mean square error than all other known filters, a maximum likelihood time difference of arrival estimator that outperformed previously optimal estimators, and a signal presence detector having a selectivity unparalleled in burst interference environments. It was further shown that these improvements resulted in a greater ability to communicate, to locate electronic transmitters, and to mitigate the effects of a growing interference environment

Kinematic and cyclostationary parameter estimation for co-channel emitter location applications

The problem of locating a signal source, or an emitter, has many civilian and military applications, such as communication regulations enforcement, military reconnaissance, and search-and-rescue operations. Many of the most widely used emitter location methods rely on the accurate and robust estimation of the differential time delay, or time-difference-of-arrival (TDOA), and the differential Doppler shift, or frequency- difference-of-arrival (FDOA), between signal replicas arriving at two spatially separated receivers. There are many conventional methods for estimating TDOA and/or FDOA. However, these methods are unable to produce unbiased TDOA and FDOA estimates when multiple emitters are located spatially close to each other. In many cases, the spatial proximity at which the conventional methods fail is still unacceptably large for precision emitter location applications. This problem is made even more diffcult when separating signals from multiple emitters that share the same regions of the spectrum at the same time. When spatially close emitters overlap spectrally and temporally, robust TDOA and FDOA estimation is diffcult, and accurate emitter location not only requires both estimation of TDOA, or FDOA, or both jointly, but also the estimation of a signal parameter that can be used to separate the signal-of-interest (SOI) from a signal(s)-not-of-interest (SNOI) that are both within the receiver's field of view. The signal separation pa- rameter selected depends on the type of signal modulation. In this thesis, the signals of interest are bauded signals. The separation methodology for such signals is cyclo- stationarity with parameterization by cyclic frequency. Based on this assumption, a new three-dimensional joint estimation method for TDOA, FDOA, and cyclic frequency parameters, called alpha cross ambiguity function (alpha-CAF), has been developed to ex- ploit signal modulations with cyclostationary properties. By exploiting cyclostationarity, alppha-CAF can produce separate unbiased TDOA and FDOA estimates that will in turn yield reliable geolocation estimates for precision emitter location applications even when severe interference causes conventional methods to fail. In this thesis the alpha-CAF param- eter estimation (TDOA, FDOA, Cyclic Frequency) algorithm is introduced along with a complete analysis of its performance compared to conventional estimators. A connection is also made between the alpha-CAF algorithm and the additional steps needed to perform an emitter location technique

Effect of multiuser interference on subscriber location in CDMA networks

The last few years have witnessed an ever growing interest in the field of mobile location systems for cellular systems. The motivation is the series of regulations passed by Federal Communications Commission, requiring that wireless service providers support a mobile telephone callback feature and cell site location mechanism. A further application of the location technology is in the rapidly emerging field of intelligent transportation systems, which are intended to enhance highway safety, location based billing etc. Many of the existing location technologies use GPS and its derivatives which require a specialized subscriber equipment. This is not feasible for popular use, as the cost of such equipments is very high. Hence, for a CDMA network, various methods have been studied that use the cellular network as the sole means to locate the mobile station (MS), where the estimates are derived from the signal transmitted by the MS to a set of base station\u27s (BS) This approach has the advantage of requiring no modifications to the subscriber equipment. While subscriber location has been previously studied for CDMA networks, the effect of multiple access interference has been ignored. In this thesis we investigate the problem of subscriber location in the presence of multiple access interference. Using MATLAB as a simulation tool, we have developed an extensive simulation technique which measures the error in location estimation for different network and user configurations. In our studies we include the effects of log-normal shadow and Rayleigh fading. We present results that illustrate the effects of varying shadowing losses, number of BS\u27s involved in position location, early-late discriminator offset and cell sizes in conjunction with the varying number of users per cell on the accuracy of radiolocation estimation

Multi-antenna non-line-of-sight identification techniques for target localization in mobile ad-hoc networks

Target localization has a wide range of military and civilian applications in wireless mobile networks. Examples include battle-field surveillance, emergency 911 (E911), traffc alert, habitat monitoring, resource allocation, routing, and disaster mitigation. Basic localization techniques include time-of-arrival (TOA), direction-of-arrival (DOA) and received-signal strength (RSS) estimation. Techniques that are proposed based on TOA and DOA are very sensitive to the availability of Line-of-sight (LOS) which is the direct path between the transmitter and the receiver. If LOS is not available, TOA and DOA estimation errors create a large localization error. In order to reduce NLOS localization error, NLOS identifcation, mitigation, and localization techniques have been proposed. This research investigates NLOS identifcation for multiple antennas radio systems. The techniques proposed in the literature mainly use one antenna element to enable NLOS identifcation. When a single antenna is utilized, limited features of the wireless channel can be exploited to identify NLOS situations. However, in DOA-based wireless localization systems, multiple antenna elements are available. In addition, multiple antenna technology has been adopted in many widely used wireless systems such as wireless LAN 802.11n and WiMAX 802.16e which are good candidates for localization based services. In this work, the potential of spatial channel information for high performance NLOS identifcation is investigated. Considering narrowband multiple antenna wireless systems, two xvNLOS identifcation techniques are proposed. Here, the implementation of spatial correlation of channel coeffcients across antenna elements as a metric for NLOS identifcation is proposed. In order to obtain the spatial correlation, a new multi-input multi-output (MIMO) channel model based on rough surface theory is proposed. This model can be used to compute the spatial correlation between the antenna pair separated by any distance. In addition, a new NLOS identifcation technique that exploits the statistics of phase difference across two antenna elements is proposed. This technique assumes the phases received across two antenna elements are uncorrelated. This assumption is validated based on the well-known circular and elliptic scattering models. Next, it is proved that the channel Rician K-factor is a function of the phase difference variance. Exploiting Rician K-factor, techniques to identify NLOS scenarios are proposed. Considering wideband multiple antenna wireless systems which use MIMO-orthogonal frequency division multiplexing (OFDM) signaling, space-time-frequency channel correlation is exploited to attain NLOS identifcation in time-varying, frequency-selective and spaceselective radio channels. Novel NLOS identi?cation measures based on space, time and frequency channel correlation are proposed and their performances are evaluated. These measures represent a better NLOS identifcation performance compared to those that only use space, time or frequency

Passive detection of moving aerial target based on multiple collaborative GPS satellites

Passive localization is an important part of intelligent surveillance in security and emergency applications. Nowadays, Global Navigation Satellite Systems (GNSSs) have been widely deployed. As a result, the satellite signal receiver may receive multiple GPS signals simultaneously, incurring echo signal detection failure. Therefore, in this paper, a passive method leveraging signals from multiple GPS satellites is proposed for moving aerial target detection. In passive detection, the first challenge is the interference caused by multiple GPS signals transmitted upon the same spectrum resources. To address this issue, successive interference cancellation (SIC) is utilized to separate and reconstruct multiple GPS signals on the reference channel. Moreover, on the monitoring channel, direct wave and multi-path interference are eliminated by extensive cancellation algorithm (ECA). After interference from multiple GPS signals is suppressed, the cycle cross ambiguity function (CCAF) of the signal on the monitoring channel is calculated and coordinate transformation method is adopted to map multiple groups of different time delay-Doppler spectrum into the distance−velocity spectrum. The detection statistics are calculated by the superposition of multiple groups of distance-velocity spectrum. Finally, the echo signal is detected based on a properly defined adaptive detection threshold. Simulation results demonstrate the effectiveness of our proposed method. They show that the detection probability of our proposed method can reach 99%, when the echo signal signal-to-noise ratio (SNR) is only −64 dB. Moreover, our proposed method can achieve 5 dB improvement over the detection method using a single GPS satellite

Target localization in passive and active systems : performance bonds

The main goal of this dissertation is to improve the understanding and to develop ways to predict the performance of localization techniques as a function of signal-to-noise ratio (SNR) and of system parameters. To this end, lower bounds on the maximum likelihood estimator (MLE) performance are studied. The Cramer-Rao lower bound (CRLB) for coherent passive localization of a near-field source is derived. It is shown through the Cramer-Rao bound that, the coherent localization systems can provide high accuracies in localization, to the order of carrier frequency of the observed signal. High accuracies come to a price of having a highly multimodal estimation metric which can lead to sidelobes competing with the mainlobe and engendering ambiguity in the selection of the correct peak. The effect of the sidelobes over the estimator performance at different SNR levels is analyzed and predicted with the use of Ziv-Zakai lower bound (ZZB). Through simulations it is shown that ZZB is tight to the MLEs performance over the whole SNR range. Moreover, the ZZB is a convenient tool to assess the coherent localization performance as a function of various system parameters. The ZZB was also used to derive a lower bound on the MSE of estimating the range and the range rate of a target in active systems. From the expression of the derived lower bound it was noted that, the ZZB is determined by SNR and by the ambiguity function (AF). Thus, the ZZB can serve as an alternative to the ambiguity function (AF) as a tool for radar design. Furthermore, the derivation is extended to the problem of estimating target’s location and velocity in a distributed multiple input multiple output (MIMO) radar system. The derived bound is determined by SNR, by the product between the number of transmitting antennas and the number of receiving antennas from the radar system, and by all the ambiguity functions and the cross-ambiguity functions corresponding to all pairs transmitter-target-receiver. Similar to the coherent localization, the ZZB can be applied to study the performance of the estimator as a function of different system parameters. Comparison between the ZZB and the MSE of the MLE obtained through simulations demonstrate that the bound is tight in all SNR regions