Javier G. Garcia

Maximum-likelihood attitude estimation using GPS signals

The maximum likelihood estimator (MLE) for a vehicles attitude using signals received from GPS satellites is derived in this paper. A statistical model of the measured phase double-differences is developed to form the likelihood function. The attitude is represented by a rotation matrix, a member of the group of 3x3 special orthogonal matrices. A steepest descent-like maximization algorithm is derived, that guarantees that the estimates belong to this manifold. Experimental results illustrate the performance and the importance of considering the right correlation between measurements.

Optimized Carrier Tracking Loop Design for Real-Time High-Dynamics GNSS Receivers

Carrier phase estimation in real-time Global Navigation Satellite System (GNSS) receivers is usually performed by tracking loops due to their very low computational complexity. We show that a careful design of these loops allows them to operate properly in high-dynamics environments, that is, accelerations up to 40 g or more. Their phase and frequency discriminators and loop filter are derived considering the digital nature of the loop inputs. Based on these ideas, we propose a new loop structure named Unambiguous Frequency-Aided Phase-Locked Loop (UFA-PLL). In terms of tracking capacity and noise resistance UFA-PLL has the same advantages of frequently used coupled-loop schemes, but it is simpler to design and to implement. Moreover, it can keep phase lock in situations where other loops cannot. The loop design is completed selecting the correlation time and loop bandwidth that minimize the pull-out probability, without relying on typical rules of thumb. Optimal and efficient ways to smooth the phase estimates are also presented. Hence, high-quality phase measurements—usually exploited in offline and quasistatic applications—become practical for real-time and high-dynamics receivers. Experiments with fixed-point implementations of the proposed loops and actual radio signals are also shown.

A high data rate BPSK receiver implementation in FPGA for high dynamics applications

In this paper we present the implementation of a FPGA based high data rate BPSK receiver specifically designed to withstand the high dynamics of airborne vehicles (i.e. aircraft, sounding rockets, satellites, etc.). The carrier recovery is implemented through a Costas loop, and a Gardner detector is used for the timing recovery. This architecture was chosen because it provides almost independent carrier and bit synchronization. Loop filters were designed through analog to discrete-time conversion. A theoretical analysis of the design, simulation and its implementation is presented.

A practical RF front-end for high performance GNSS receivers

We present the design and implementation of a GNSS front-end intended for receiving the L1/E1 band of GPS/Galileo and GLONASS signals. The proposed scheme consists of a radio frequency (RF) stage, with a low noise amplifier which has a noise figure of 1.1dB. Then, the RF signals are down-converted to an intermediate frequency, where the GPS/Galileo and GLONASS bands are separated. Thanks to this separation, a considerable reduction of the necessary sampling rate for the digitalization stage is achieved. This simplifies and reduces the power consumption of this stage of the complete GNSS receiver. The present design is versatile since it can be used to receive signals from the L2 band by replacing only a few components, without the necessity of modifying the printed circuit board. Measurements realized to an implemented prototype that validate the proposed design are presented.

Pull-Out Probability Considerations in High Dynamics GNSS Tracking Loops Design

In this paper approximated expressions for the pull- out probability of digital tracking loops are derived. The analysis is done for a PLL and for a UFA-PLL recently introduced in P.A. Roncagliolo and J.G. Garcia (2007), as a structure for high dynamic applications. The considered dynamics is modeled as acceleration steps and the loop filter used is designed with a fully digital technique presented previously. These expressions allow to quantify the role of the different loop parameters, such as the integration time and loop bandwidth, at the design stage and to choose them more efficiently. Monte Carlo simulations for 20 g acceleration steps showing the usefulness and limitations of these approximations are presented.

An Experimental L1/L2 GNSS Receiver for High Precision Applications

In this work we present the design and implementation of a GNSS receiver that can work with the civil signals of the L1 and L2 bands of GPS and GLONASS, and the E1 Open Service signal of Galileo. The developed prototype has two RF front-ends, one for the L1 band and another for the L2 band. The signals from each band are amplified and then down-converted to an intermediate frequency. The two local oscillator tones used for the mixing, and the clock signals for the next digitalization and processing stages are generated by a frequency synthesizer board, from a common reference. The digitalization and posterior processing of the signals can be carried out using generic devices, like an acquisition board and an FPGA, according to the Software Defined Radio (SDR) concept. In this way a programmable receiver is obtained. These kinds of receivers are versatile since they can be used for testing acquisition, tracking, and navigation algorithms for research and develop purposes. Commercial receivers do not have that capability, because their digital processing stages cannot be modified by the user. Moreover, a multi-band and multi-constellation receiver allows to greatly increase the performance in relation to mass market GNSS receivers which relay on only one navigation system and one carrier frequency. Measurements realized to the implemented prototype that validate the proposed design are presented.

A joint carrier and data estimation scheme for real-time high dynamics GNSS receivers

Real-time GNSS receivers usually track the navigation satellite signals by means of code and carrier loops. In previous works we derived optimum loop filters and introduced the UFA discriminator to improve the PLL response to acceleration steps expected in launching vehicles. In this paper we present a data detection strategy based on the Per Survivor Processing (PSP) technique to use a four quadrants angle phase discriminator. The proposed scheme makes use of two parallel tracking loops and commutes between them based on the data decisions. Simulations show that 30g steps can be efficiently tracked with signal levels as low as C/N0 = 28 dB-Hz. The performance is similar to the obtained with more complex schemes and represents a 4 dB reduction in tracking threshold with respect to the single loop estimator.

A Bayesian Technique for Real and Integer Parameters Estimation in Linear Models and Its Application to GNSS High Precision Positioning

A novel Bayesian technique for the joint estimation of real and integer parameters in a linear measurement model is presented. The integer parameters take values on a finite set, and the real ones are assumed to be a Gaussian random vector. The posterior distribution of these parameters is sequentially determined as new measurements are incorporated. This is a mixed distribution with a Gaussian continuous part and a discrete one. Estimators for the integer and real parameters are derived from this posterior distribution. A Maximum A Posteriori (MAP) estimator modified with the addition of a confidence threshold is used for the integer part and a Minimum Mean Squared Error (MMSE) is used for the real parameters. Two different cases are addressed: i) both real and integer parameters are time invariant and ii) the integer parameters are time invariant but the real ones are time varying. Our technique is applied to the GNSS carrier phase ambiguity resolution problem, that is key for high precision positioning applications. The good performance of the proposed technique is illustrated through simulations in different scenarios where different kind of measurements as well as different satellite visibility conditions are considered. Comparisons with state-of-the-art ambiguity solving algorithms confirm performance improvement. The new method is shown to be useful not only in the estimation stage but also for validating the estimates ensuring a predefined success rate through proper threshold selection.

An statistical filtering models comparison for GNSS LEO satellite navigation

In this work the performance of different statistical filtering models used for estimating states of aerospace vehicles, particularly LEO satellites, based on measurements of GNSS systems are compared. This problem is non-linear in nature, since both the state variables model and the output function are non-linear. Thus we resort to the use of the extension of the Kalman filter called EKF. Different models based on several kinematic and dynamic approaches are considered. For the performance assessment we use representative simulation scenarios. Finally, as a real application example, the case of GPS measurements taken on board the Argentine SAC-D satellite is analyzed.

Comparación de Métodos de Filtrado Estadístico para Navegación de Satélites LEO con Señales GNSS

In this paper two methods of statistical filtering for satellite navigation in low earth orbit (LEO) with GNSS signals are compared. This problem is of a nonlinear nature, because both the state variables model and the output function are nonlinear. Hence, this is usually handled via extensions to the Kalman Filter. Two such variants of extended Kalman filter are compared, one that uses GNSS measurements directly and other that solves the nonlinearity states/measurements prior to the filtering. The latter can be thought of as a variant of the socalled Positioning Kalman Filtering (PKF), while maintaining the nonlinear state model.