Analysis of Multipath Mitigation Techniques with Land Mobile Satellite Channel Model

Multipath is undesirable for Global Navigation Satellite System (GNSS) receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS) path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this is of utmost importance to analyze the performance of different multipath mitigation techniques in some realistic measurement-based channel models, for example, the Land Multipath is undesirable for Global Navigation Satellite System (GNSS) receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS) path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this is of utmost importance to analyze the performance of different multipath mitigation techniques in some realistic measurement-based channel models, for example, the Land Mobile Satellite (LMS) channel model [1]-[4], developed at the German Aerospace Center (DLR). The DLR LMS channel model is widely used for simulating the positioning accuracy of mobile satellite navigation receivers in urban outdoor scenarios. The main objective of this paper is to present a comprehensive analysis of some of the most promising techniques with the DLR LMS channel model in varying multipath scenarios. Four multipath mitigation techniques are chosen herein for performance comparison, namely, the narrow Early-Minus-Late (nEML), the High Resolution Correlator, the C/N0-based two stage delay tracking technique, and the Reduced Search Space Maximum Likelihood (RSSML) delay estimator. The first two techniques are the most popular and traditional ones used in nowadays GNSS receivers, whereas the later two techniques are comparatively new and are advanced techniques, recently proposed by the authors. In addition, the implementation of the RSSML is optimized here for a narrow-bandwidth receiver configuration in the sense that it now requires a significantly less number of correlators and memory than its original implementation. The simulation results show that the reduced-complexity RSSML achieves the best multipath mitigation performance in moderate-to-good carrier-to-noise density ratio with the DLR LMS channel model in varying multipath scenarios

A new multipath mitigation method for GNSS receivers based on antenna array

the potential of small antenna array for multipath mitigation in GNSS systems is considered in this paper. To discriminate the different incoming signals (Line of sight and multipaths), a new implementation of the well known SAGE algorithm is proposed. This allows a significant complexity reduction and it is fully compatible with conventional GNSS receivers. Theoretical study thanks to the Cramer Rao Bound derivation and tracking simulation results (in static and dynamic scenarios) show that the proposed method is a very promising approach for the multipath mitigation problem in GNSS receivers

Advanced array processing techniques and systems

Research and development on smart antennas, which are recognized as a promising technique to improve the performance of mobile communications, have been extensive in the recent years. Smart antennas combine multiple antenna elements with a signal processing capability in both space and time to optimize its radiation and reception pattern automatically in response to the signal environment. This paper concentrates on the signal processing aspects of smart antenna systems. Smart antennas are often classified as either switched-beam or adaptive-array systems, for which a variety of algorithms have been developed to enhance the signal of interest and reject the interference. The antenna systems need to differentiate the desired signal from the interference, and normally requires either a priori knowledge or the signal direction to achieve its goal. There exists a variety of methods for direction of arrival (DOA) estimation with conflicting demands of accuracy and computation. Similarly, there are many algorithms to compute array weights to direct the maximum radiation of the array pattern toward the signal and place nulls toward the interference, each with its convergence property and computational complexity. This paper discusses some of the typical algorithms for DOA estimation and beamforming. The concept and details of each algorithm are provided. Smart antennas can significantly help in improving the performance of communication systems by increasing channel capacity and spectrum efficiency, extending range coverage, multiplexing channels with spatial division multiple access (SDMA), and compensating electronically for aperture distortion. They also reduce delay spread, multipath fading, co-channel interference, system complexity, bit error rates, and outage probability. In addition, smart antennas can locate mobile units or assist the location determination through DOA and range estimation. This capability can support and benefit many location-based services including emergency assistance, tracking services, safety services, billing services, and information services such as navigation, weather, traffic, and directory assistance

GPS Multipath Detection in the Frequency Domain

Multipath is among the major sources of errors in precise positioning using GPS and continues to be extensively studied. Two Fast Fourier Transform (FFT)-based detectors are presented in this paper as GPS multipath detection techniques. The detectors are formulated as binary hypothesis tests under the assumption that the multipath exists for a sufficient time frame that allows its detection based on the quadrature arm of the coherent Early-minus-Late discriminator (Q EmL) for a scalar tracking loop (STL) or on the quadrature (Q EmL) and/or in-phase arm (I EmL) for a vector tracking loop (VTL), using an observation window of N samples. Performance analysis of the suggested detectors is done on multipath signal data acquired from the multipath environment simulator developed by the German Aerospace Centre (DLR) as well as on multipath data from real GPS signals. Application of the detection tests to correlator outputs of scalar and vector tracking loops shows that they may be used to exclude multipath contaminated satellites from the navigation solution. These detection techniques can be extended to other Global Navigation Satellite Systems (GNSS) such as GLONASS, Galileo and Beidou.Comment: 2016 European Navigation Conference (ENC 2016), May 2016, Helsinki, Finland. Proceedings of the 2016 European Navigation Conference (ENC 2016

Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays

Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies - once viewed prohibitively complicated and costly - is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin

Advanced Multipath Mitigation Techniques for Satellite-Based Positioning Applications

Multipath remains a dominant source of ranging errors in Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS) or the future European satellite navigation system Galileo. Multipath is generally considered undesirable in the context of GNSS, since the reception of multipath can make significant distortion to the shape of the correlation function used for time delay estimation. However, some wireless communications techniques exploit multipath in order to provide signal diversity though in GNSS, the major challenge is to effectively mitigate the multipath, since we are interested only in the satellite-receiver transit time offset of the Line-Of-Sight (LOS) signal for the receiver's position estimate. Therefore, the multipath problem has been approached from several directions in order to mitigate the impact of multipath on navigation receivers, including the development of novel signal processing techniques. In this paper, we propose a maximum likelihood-based technique, namely, the Reduced Search Space Maximum Likelihood (RSSML) delay estimator, which is capable of mitigating the multipath effects reasonably well at the expense of increased complexity. The proposed RSSML attempts to compensate the multipath error contribution by performing a nonlinear curve fit on the input correlation function, which finds a perfect match from a set of ideal reference correlation functions with certain amplitude(s), phase(s), and delay(s) of the multipath signal. It also incorporates a threshold-based peak detection method, which eventually reduces the code-delay search space significantly. However, the downfall of RSSML is the memory requirement which it uses to store the reference correlation functions. The multipath performance of other delay-tracking methods previously studied for Binary Phase Shift Keying-(BPSK-) and Sine Binary Offset Carrier- (SinBOC-) modulated signals is also analyzed in closed loop model with the new Composite BOC (CBOC) modulation chosen for Galileo E1 signal. The simulation results show that the RSSML achieves the best multipath mitigation performance in a uniformly distributed two-to-four paths Rayleigh fading channel model for all three modulated signals