GNSS reflectrometry offers a low cost alternative for Earth remote sensing and is used to measure, for example, ocean altimetry, wind speed, wind direction and modeling of the ocean surface state. A bistatic configuration, using one right-handed circular polarized and one left-handed circular polarized antenna, was built for this experiment in order to measure direct and reflected L1 and L5 signals. The direct and reflected signals were compared and the path difference between them calculated, leading to altitude measurements with both L1 and L5 signals. Compared to publicly available signals on L1, the higher code rate of L5 will provide higher measurement sensitivity

Traction control for off-road vehicles such as articulated all-wheel drive haulers is of great importance to improve the vehicle performance. A well-known method to reduce the slip and thereby improve the traction is to engage differential locks in the driveline of the vehicle. The drawbacks of differential locks engaged are for instance increased wear, increased fuel consumption but also reduced turnability of the vehicle. Therefore, the differentials should be locked only when necessary, ideally only when slip occurs or is about to occur. A number of methods to detect slip has been reported in the literature. Some of them utilize dynamical models of the vehicle where side-slip angles are important inputs. This paper describes an off-line estimator for the side-slip angles of an articulated vehicle based on measurements from Global Positioning System (GPS) and Inertial Navigation System (INS). The current implementation is a proof of concept and the intention is to develop a system that can be used as a reference for on-line estimators. By comparing measurements from two GPS/INS units, mounted on the front and rear part of the vehicle, it is possible to estimate the side-slip angles of both the front and rear part. The method has been tested on a Volvo A25E articulated all-wheel drive hauler equipped with two high precision GPS/INS units (NovAtel's SPAN-CPT). Tests have been performed when driving on asphalt, gravel and snow. The results from the tests are discussed.

This thesis presents contributions in the field of satellite navigation with a focus on array processing and related implementation issues. For readers not familiar with GNSS, it also includes a brief overview of satellite navigation.Compared to the state of the art only ten years ago, modern GNSS receivers are very capable. One reason for this improvement is advances in the semiconductor industry that have increased both the available processing power and the energy efficiency. An active research community have also made important contributions resulting in more sophisticated algorithms. To improve receiver performance even further, auxiliary sensors such as gyros and accelerometers are becoming increasingly common. A related option involves using an antenna with several physical elements. This is known as an antenna array and is often used for radar, sonar and telecommunication applications. Array processing can also be used for GNSS and as such it is the primary focus of this thesis. An array allows for exploration of the spatial domain, in other words a receiver that may differentiate between signals depending on the direction of arrival. For GNSS, where interference and multipath (signal reflection off, for example, buildings or the ground) may be significant sources of error, this is an attractive solution. Although array processing have been the subject of extensive research efforts within other fields, there are several remaining issues with regards to how these techniques can be implemented in a GNSS receiver.With regards to array processing there are also properties unique to GNSS, such as multiple signal sources at known positions, that have not been explored sufficiently in previous efforts. In this thesis we show how these properties can be exploited to improve receiver performance in dynamic scenarios. In short, the orientation of the antenna platform is estimated accurately (typical variance around 1°) using beamforming techniques. This information is then used to achieve a better estimate of the radio environment by allowing for longer integration periods when estimating the covariance matrices. A better estimate of the covariance matrices directly translates into improved receiver performance, especially so in areas of moderate levels of multipath/interference.Further, a method to calibrate GNSS array antennas using real signals is investigated in detail. Instead of resorting to electromagnetic simulations that requires precise knowledge about the antenna and installation factors, or RF chamber measurement that is expensive, it is shown how the array antenna can be calibrated using live signals. The accuracy of the resulting model is verified using real data.Also, the first implementation of an RF record and replay system is presented. With such a system data can be recorded in a specific environment, generally a time consuming task, and later played back into the antenna input of any GNSS receiver. Such systems are nowadays commercially available and have proven very useful for testing and validation of GNSS receivers. Throughout the thesis, the required receiver architecture and practical viability of the proposed algorithms are considered.

Although GNSS RF signal simulators have long possessed the capability to generate scenarios they are, for example, not yet able to model a realistic scenario with complex multipath. Software defined receivers bridge the gap between simulated and real data to the extent that they may offer a replay capability, where a data set is first recorded to disk and later can be processed several times. Unfortunately, the recorded data generally can not be used by other GNSS receivers, making receiver to receiver comparisons difficult and time consuming.This paper describes a system capable of replaying recorded IF data into any narrow bandwidth L1 GNSS receiver, including an evaluation of the difference (position, timing and SNR) between live and replayed data using a high sensitivity, consumer grade receiver. The performance of the replayed data set was found to match that of the live data.

Precipitation in the form of snow or rain could severely degrade the performance of large antenna arrays, in particular if knowledge about the beam shape and pointing direction in absolute numbers is necessary. In this paper, a method of estimating the far-field of each individual antenna element using the equivalent electric current approach is presented. Both a least squares estimator and a Kalman filter was used to solve the resulting system of equation and their performance was compared. Simulation results shows that the estimated far-field for one antenna element is very accurate if there is no noise on the signal. During noisier conditions the Kalman filter gives less noisy results while the systematic errors are slightly larger compared to the least squares estimator.

Software defined receivers (SDR) are an increasingly important tool within the GNSS research community as the high level of flexibility offer a significant advantage over traditional hardware implementations. Over the last decade, software receivers have been used to investigate techniques as diverse as bi-static radar (additional correlators), multipath mitigation techniques, GPS/INS integration and array processing.Mentioned above are only a few examples of features that could be required of an SDR, other include support for new signals (Galileo, GPS L5), multiple data file formats, high sensitivity and support for very long data sets. The large number of available features should ideally be coupled with program simplicity (such that other people can understand the program) and efficiency. This paper discusses these issues and proposes several solutions such asgeneralized data buffers (that is trivial to extend for new data formats) and a unified tracking structure (regardless of signal modulation). Examples are given using a Matlab implementation based on the Borre/Akos book Ä Software-Defined GPS and Galileo Receiver", however with significant modifications. Where critical, Java is used to increase performance while maintaining cross platform compatibility. Near real-time operation is available under optimal circumstances and the receiver currently supports GPS C/A- and GPS P-code signals.

When using antenna arrays with GNSS receivers both the gain and the phase of the far-field radiation pattern may be distorted due to coupling effects. This problem can often be characterized in the design process of the antenna or by measurements in a measurement range. This is, however, not always possible and it is then necessary to characterize the antenna using live measurements. In this paper the equivalent electric current method is used to estimate the gain and phase of the far-field of an antenna array for a GPS receiver. In the method, the complex far-field pattern of an antenna is estimated using the distribution of the electric current, which is described using suitable basis functions. The method was evaluated using data collected by a 7-element GPS antenna array. The results show agreement between the model and measured results.

A key parameter of GNSS receiver performance is the sensitivity, meaning how weak signals the receiver can acquire and track. For acquisition, this is typically measured by the minimum signal strength that can be detected with a certain probability. In this paper, a novel method of computing the probability of detection is presented. In contrast with prevailing techniques, it takes receiver parameters such as correlator and doppler spacing into account when computing the probability distribution function. The likelihood of data bit switches inside the correlation window is also considered in a similar fashion. The method is demonstrated both on a traditional correlator architecture, and on two different FFT based acquisition algorithms, coherent and non-coherent. Further, the computational complexity of the different algorithms is evaluated for a general computing platform. The combination of these two methods provide valuable insight into the problem of minimizing power consumption while maximizing sensitivity for software based GNSS receivers.

An array processing GNSS (Global Navigation Satellite System) receiver may provide increased accuracy, reliability and integrity by forming beams towards satellites and nulls towards interference or reflective surfaces. Also, software defined receivers have proven themselves versatile and provide a convenient environment to implement novel algorithms.This paper first describes the gain/phase calibration of a seven element custom array antenna and proceeds to compare the single antenna performance to that of the performance attained by forming beams towards the satellites. IF (Intermediate Frequency) data, high rate samples representing the received signal in a narrow band around the GPS L1 frequency, from an array antenna have been recorded both in an environment with open sky conditions and also in more challenging areas (central Boulder, Colorado). Simultaneously, data from a high quality GPS based INS was recorded in order to obtain accurate estimates of position/ orientation. Calibration of the system (including antennas and front-ends) was performed using data from the benign environment, and based on this information, deterministic beams were formed towards the satellites using data from the semi-urban dataset. The single antenna accuracy was then compared to the position obtained by processing after forming beams.

Since the very first Global Positioning System satellite was launched in 1978, Global Navigation Satellite Systems (GNSS) have developed into a world wide utility, providing everyone with an affordable method for determining accurate position and time. However, the system is susceptible to multipath (when the signal is reflected off a surface), interference (other signals in the same frequency band) and attenuation (for example canopies blocking some of the signal energy). Array processing of GNSS signals have lately drawn quite a bit of attention from the research community, where issues (susceptibility to interference, multipath and attenuation) can be mitiged to some degree. GNSS baseband processing is generally implemented in hardware (digital logic), although software based processing are swiftly gaining popularity among researchers. This thesis discusses the implementation of a software based GNSS array processing system with an emphasis on hardware, calibration and initial signal detection. Low cost, ASIC based front-ends are examined with regards to phase and gain stability, and are found to meet the requirements for array processing of GNSS signals. An antenna calibration technique using live GNSS signals (as opposed to anechoic chamber measurements) is proposed, where the predictable orbits and geometric diversity of GNSS are exploited. A system capable of replaying recorded narrow band GNSS signals into any low cost receiver is also discussed. Finally, efficient methods to acquire GNSS signals using an antenna array system are proposed.