Analysis of Ionospheric Scintillations using Wideband GPS L1 C/A Signal Data

A non-real-time GPS receiver has been developed and tested for use in scintillation analysis. The receiver consists of a digital storage receiver and non-real-time software acquisition and tracking algorithms. The goal of this work is to shed light on the behavior of strongly scintillating signals: signals which cause conventional GPS receivers to lose carrier lock. The receiver collects wideband GPS L1 digital data sampled at 5.7 MHz using an RF front-end and stores it on disk for post-processing. It processes the data off-line to determine carrier signal amplitude and phase variations during scintillations. The main processing algorithms are traditional code delay and carrier frequency acquisition algorithms and special signal processing algorithms that effectively function as a delay-locked loop and phase-locked loop. The tracking algorithms use non-causal smoothing techniques in order to optimally reconstruct the phase and amplitude variations of a scintillating signal. These techniques are robust against the deep power fades and strong phase fluctuations characteristic of scintillating signals. To test the receiver, scintillation data were collected in Cauchoeira Paulista, Brazil, from December 4 to 6, 2003. The data set spans several hours and includes times when one or more satellite signals are scintillating. The smoothing algorithm has been used to determine the carrier amplitude and phase time histories of the scintillating signals along with the distortion of the pseudorandom noise (PRN) code’s autocorrelation function. These quantities provide a characterization of scintillation that can be used to study the physics of scintillations or to provide off-line test cases to evaluate a tracking algorithm’s ability to maintain signal lock during scintillations.Aerospace Engineering and Engineering Mechanic

GPS Carrier Tracking Loop Performance in the presence of Ionospheric Scintillations

The performance of several GPS carrier tracking loops is evaluated using wideband GPS data recorded during strong ionospheric scintillations. The aim of this study is to determine the loop structures and parameters that enable good phase tracking during the power fades and phase dynamics induced by scintillations. Constant-bandwidth and variable-bandwidth loops are studied using theoretical models, simulation, and tests with actual GPS signals. Constant-bandwidth loops with loop bandwidths near 15 Hz are shown to lose phase lock during scintillations. Use of the decision-directed discriminator reduces the carrier lock threshold by ∼1 dB relative to the arctangent and conventional Costas discriminators. A proposed variablebandwidth loop based on a Kalman filter reduces the carrier lock threshold by more than 7 dB compared to a 15-Hz constant-bandwidth loop. The Kalman filter-based strategy employs a soft-decision discriminator, explicitly models the effects of receiver clock noise, and optimally adapts the loop bandwidth to the carrier-to-noise ratio. In extensive simulation and in tests using actual wideband GPS data, the Kalman filter PLL demonstrates improved cycle slip immunity relative to constant bandwidth PLLs.Aerospace Engineering and Engineering Mechanic

Review of Unbiased FIR Filters, Smoothers, and Predictors for Polynomial Signals

Extracting an estimate of a slowly varying signal corrupted by noise is a common task. Examples can be found in industrial, scientific and biomedical instrumentation. Depending on the nature of the application the signal estimate is allowed to be a delayed estimate of the original signal or, in the other extreme, no delay is tolerated. These cases are commonly referred to as filtering, prediction, and smoothing depending on the amount of advance or lag between the input data set and the output data set. In this review paper we provide a comprehensive set of design and analysis tools for designing unbiased FIR filters, predictors, and smoothers for slowly varying signals, i.e. signals that can be modeled by low order polynomials. Explicit expressions of parameters needed in practical implementations are given. Real life examples are provided including cases where the method is extended to signals that are piecewise slowly varying. A critical view on recursive implementations of the algorithms is provided

Robust Positioning in the Presence of Multipath and NLOS GNSS Signals

GNSS signals can be blocked and reflected by nearby objects, such as buildings, walls, and vehicles. They can also be reflected by the ground and by water. These effects are the dominant source of GNSS positioning errors in dense urban environments, though they can have an impact almost anywhere. Non- line-of-sight (NLOS) reception occurs when the direct path from the transmitter to the receiver is blocked and signals are received only via a reflected path. Multipath interference occurs, as the name suggests, when a signal is received via multiple paths. This can be via the direct path and one or more reflected paths, or it can be via multiple reflected paths. As their error characteristics are different, NLOS and multipath interference typically require different mitigation techniques, though some techniques are applicable to both. Antenna design and advanced receiver signal processing techniques can substantially reduce multipath errors. Unless an antenna array is used, NLOS reception has to be detected using the receiver's ranging and carrier-power-to-noise-density ratio (C/N0) measurements and mitigated within the positioning algorithm. Some NLOS mitigation techniques can also be used to combat severe multipath interference. Multipath interference, but not NLOS reception, can also be mitigated by comparing or combining code and carrier measurements, comparing ranging and C/N0 measurements from signals on different frequencies, and analyzing the time evolution of the ranging and C/N0 measurements

Channel, Phase Noise, and Frequency Offset in OFDM Systems: Joint Estimation, Data Detection, and Hybrid Cramer-Rao Lower Bound

Oscillator phase noise (PHN) and carrier frequency offset (CFO) can adversely impact the performance of orthogonal frequency division multiplexing (OFDM) systems, since they can result in inter carrier interference and rotation of the signal constellation. In this paper, we propose an expectation conditional maximization (ECM) based algorithm for joint estimation of channel, PHN, and CFO in OFDM systems. We present the signal model for the estimation problem and derive the hybrid Cramer-Rao lower bound (HCRB) for the joint estimation problem. Next, we propose an iterative receiver based on an extended Kalman filter for joint data detection and PHN tracking. Numerical results show that, compared to existing algorithms, the performance of the proposed ECM-based estimator is closer to the derived HCRB and outperforms the existing estimation algorithms at moderate-to-high signal-to-noise ratio (SNR). In addition, the combined estimation algorithm and iterative receiver are more computationally efficient than existing algorithms and result in improved average uncoded and coded bit error rate (BER) performance

Tightly-Coupled Opportunistic Navigation for Deep Urban and Indoor Positioning

A strategy is presented for exploiting the frequency stability, transmit location, and timing information of ambient radio-frequency “signals of opportunity” for the purpose of navigating in deep urban and indoor environments. The strategy, referred to as tightly-coupled opportunistic navigation (TCON), involves a receiver continually searching for signals from which to extract navigation and timing information. The receiver begins by characterizing these signals, whether downloading characterizations from a collaborative online database or performing characterizations on-the-fly. Signal observables are subsequently combined within a central estimator to produce an optimal estimate of position and time. A simple demonstration of the TCON strategy focused on timing shows that a TCONenabled receiver can characterize and use CDMA cellular signals to correct its local clock variations, allowing it to coherently integrate GNSS signals beyond 100 seconds.Aerospace Engineering and Engineering Mechanic