Multipath and interference errors reduction in gps using antenna arrays

The Global Positioning System (GPS) is a worldwide satellite based positioning system that provides any user with tridimensional position, speed and time information. The measured pseudorange is affected by the multipath propagation, which probably is the major source of errors for high precision systems. After a presentation of the GPS and the basic techniques employed to perform pseudorange measurements, the influence of the multipath components on the pseudorange measurement is explained. Like every system the GPS is also exposed to the errors that can be caused by the interferences, and a lot of civil applications need robust receivers to interferences for reasons of safety. In this paper some signal array processing techniques for reducing the code measurement errors due to the multipath propagation and the interferences are presented. Firstly, a non-adaptive beamforming is used. Secondly, a variant of the MUSIC and the maximum likelihood estimator can be used to estimate the DOA of the reflections and the interferences, and then a weight vector that removes these signals is calculated. In the third place, a beamforming with temporal reference is presented; the reference is not the GPS signal itself, but the output of a matched filter to the code. An interesting feature of the proposed techniques is that they can be applied to an array of arbitrary geometry.Peer ReviewedPostprint (published version

Space Time MUSIC: Consistent Signal Subspace Estimation for Wide-band Sensor Arrays

Wide-band Direction of Arrival (DOA) estimation with sensor arrays is an essential task in sonar, radar, acoustics, biomedical and multimedia applications. Many state of the art wide-band DOA estimators coherently process frequency binned array outputs by approximate Maximum Likelihood, Weighted Subspace Fitting or focusing techniques. This paper shows that bin signals obtained by filter-bank approaches do not obey the finite rank narrow-band array model, because spectral leakage and the change of the array response with frequency within the bin create \emph{ghost sources} dependent on the particular realization of the source process. Therefore, existing DOA estimators based on binning cannot claim consistency even with the perfect knowledge of the array response. In this work, a more realistic array model with a finite length of the sensor impulse responses is assumed, which still has finite rank under a space-time formulation. It is shown that signal subspaces at arbitrary frequencies can be consistently recovered under mild conditions by applying MUSIC-type (ST-MUSIC) estimators to the dominant eigenvectors of the wide-band space-time sensor cross-correlation matrix. A novel Maximum Likelihood based ST-MUSIC subspace estimate is developed in order to recover consistency. The number of sources active at each frequency are estimated by Information Theoretic Criteria. The sample ST-MUSIC subspaces can be fed to any subspace fitting DOA estimator at single or multiple frequencies. Simulations confirm that the new technique clearly outperforms binning approaches at sufficiently high signal to noise ratio, when model mismatches exceed the noise floor.Comment: 15 pages, 10 figures. Accepted in a revised form by the IEEE Trans. on Signal Processing on 12 February 1918. @IEEE201

Sensor array signal processing : two decades later

Caption title.Includes bibliographical references (p. 55-65).Supported by Army Research Office. DAAL03-92-G-115 Supported by the Air Force Office of Scientific Research. F49620-92-J-2002 Supported by the National Science Foundation. MIP-9015281 Supported by the ONR. N00014-91-J-1967 Supported by the AFOSR. F49620-93-1-0102Hamid Krim, Mats Viberg

Accurate DOA Estimation for Large-Scale Uniform Circular Array Using a Single Snapshot

© 1997-2012 IEEE. A large-scale antenna array is an enabling technique for millimeter-wave communications. Uniform circular arrays (UCAs) have the spatial invariance property, ensuring the same beamforming performance in the whole angular region. However, the direction-of-arrival (DOA) estimation in UCAs is challenging since the array response of a UCA does not conform to a Vandermonde structure as that of a uniform linear array. This letter proposes an accurate and low-complexity DOA estimation approach by exploiting the good correlation property of the array response of the UCA. The DOA estimates are first obtained from a circular convolution between a single snapshot and the designed coefficient vector. Then, by searching for the best initial phase of the coefficient vector, the DOA estimates can be refined to a configurable accuracy. The simulation results demonstrate that the proposed approach outperforms the state of the art by orders of magnitude in estimation accuracy

Deterministic Cramer-Rao bound for strictly non-circular sources and analytical analysis of the achievable gains

Recently, several high-resolution parameter estimation algorithms have been developed to exploit the structure of strictly second-order (SO) non-circular (NC) signals. They achieve a higher estimation accuracy and can resolve up to twice as many signal sources compared to the traditional methods for arbitrary signals. In this paper, as a benchmark for these NC methods, we derive the closed-form deterministic R-D NC Cramer-Rao bound (NC CRB) for the multi-dimensional parameter estimation of strictly non-circular (rectilinear) signal sources. Assuming a separable centro-symmetric R-D array, we show that in some special cases, the deterministic R-D NC CRB reduces to the existing deterministic R-D CRB for arbitrary signals. This suggests that no gain from strictly non-circular sources (NC gain) can be achieved in these cases. For more general scenarios, finding an analytical expression of the NC gain for an arbitrary number of sources is very challenging. Thus, in this paper, we simplify the derived NC CRB and the existing CRB for the special case of two closely-spaced strictly non-circular sources captured by a uniform linear array (ULA). Subsequently, we use these simplified CRB expressions to analytically compute the maximum achievable asymptotic NC gain for the considered two source case. The resulting expression only depends on the various physical parameters and we find the conditions that provide the largest NC gain for two sources. Our analysis is supported by extensive simulation results.Comment: submitted to IEEE Transactions on Signal Processing, 13 pages, 4 figure

Estimation and Minimization of the Cramer-Rao lower bound for radio direction-finding on the azimuth and elevation of planar antenna arrays

In this paper an approach of obtaining optimal planar antenna arrays consisting of omnidirectional sensors is proposed. The novelty of the proposed approach is to apply an exact expression of the Cramer-Rao lower bound for an arbitrary planar antenna array consisting of a number of omnidirectional elements which has been presented in the further chapters of the paper. The obtained formula describes the influence of antenna elements locations on the direction-of-arrival estimation accuracy. It has been shown that the direction-of-arrival accuracy via planar antenna arrays is determined as the sum of squares of differences between all omnidirectional elements coordinates along x- and y-axis. Thus knowing an expected area or sector of signal source it is very easy to calculate optimal arrangement of antenna elements in order to reduce direction-finding errors, because obtained by that way positions gives the best match according to the maximum likelihood criterion. It is worth nothing that such antenna arrays are useful in the way that they allow estimating the coordinates of radio emission sources in the three-dimensional coordinate space, i.e. in azimuth and elevation. In order to confirm the proposed methodology optimal antenna arrays constructed after minimization of the new formulas are researched. It is found out that the new shapes of antenna arrays based on the analytical expressions have better direction-of-arrival accuracy in comparison with the circular ones

Mutual Coupling in Phased Arrays: A Review

The mutual coupling between antenna elements affects the antenna parameters like terminal impedances, reflection coefficients and hence the antenna array performance in terms of radiation characteristics, output signal-to-interference noise ratio (SINR), and radar cross section (RCS). This coupling effect is also known to directly or indirectly influence the steady state and transient response, the resolution capability, interference rejection, and direction-of-arrival (DOA) estimation competence of the array. Researchers have proposed several techniques and designs for optimal performance of phased array in a given signal environment, counteracting the coupling effect. This paper presents a comprehensive review of the methods that model and mitigate the mutual coupling effect for different types of arrays. The parameters that get affected due to the presence of coupling thereby degrading the array performance are discussed. The techniques for optimization of the antenna characteristics in the presence of coupling are also included

Topics in the accuracy and resolution of superresolution systems

Since their introduction in the 1970s and 1980s superresolution systems for point source parameter estimation have received theoretical attention regarding their potential performance. Two aspects of performance in particular are of interest, the accuracy of the parameter estimation and the resolution achievable. Limitations on performance may be considered to be due to noise affecting the data, or to errors in the system. Superresolution methods divide roughly into two groups – ‘spectral’ methods and maximum likelihood (ML) methods. MUSIC is perhaps the most effective example of a spectral method and has been studied in considerable detail, in both performance measures, but mainly only for the case of a single parameter. In this study the accuracy of MUSIC in the application of two-dimensional direction finding (DF) has been analysed, with and without system errors, using a general array. Theoretical results are confirmed by simulations. An aim has been to produce simpler results for use in estimating the potential performance of practical systems. Little work has been reported on the resolution of ML methods and this is the second main topic of this work, particularly for the two-dimensional DF case using a general array, with a ML method (IMP) similar to the better known Alternating Projection. Some results are obtained for resolution with and without errors for the case of noncoherent signals. For coherent signals (including the standard radar case) the performance is found to depend on the relative phase of the signals, varying from the quadrature case, where the performance is as for the non-coherent case, to the in-phase (or antiphase) case where only one signal peak is seen