Global Navigation Satellite System Signal Acquisition Research Articles

Navigating latency hurdles: an in-depth examination of a cloud-powered GNSS real-time positioning application on mobile devices.

A growing dependence on real-time positioning apps for navigation, safety, and location-based services necessitates a deep understanding of latency challenges within cloud-based Global Navigation Satellite System (GNSS) solutions. This study analyses a GNSS real-time positioning app on smartphones that utilizes cloud computing for positioning data delivery. The study investigates and quantifies diverse latency contributors throughout the system architecture, including GNSS signal acquisition, data transmission, cloud processing, and result dissemination. Controlled experiments and real-world scenarios are employed to assess the influence of network conditions, device capabilities, and cloud server load on overall positioning latency. Findings highlight system bottlenecks and their relative contributions to latency. Additionally, practical recommendations are presented for developers and cloud service providers to mitigate these challenges and guarantee an optimal user experience for real-time positioning applications. This study not only elucidates the complex interplay of factors affecting GNSS app latency, but also paves the way for future advancements in cloud-based positioning solutions, ensuring the accuracy and timeliness critical for safety-critical and emerging applications.

A Novel GNSS Sweep Interference Detection and Mitigation Method Based on Radon–Wigner Transform

In this paper, a novel Radon-Wigner transform (RWT) based sweep interference detection and mitigation method has been proposed for global navigation satellite system (GNSS) receivers working in the disturbing scenarios. The proposed GNSS sweep interference detection and mitigation method has been tested using real GPS L1-C/A data disturbed by the sweep interference in a controlled test bench experiment. The results have shown that the proposed method can effectively deal with the cross-term problems with the conventional time-frequency (TF) analysis techniques and provide much improved GNSS interference detection performance in comparison to the existed Wigner-Ville distribution (WVD) and Wigner-Hough transform (WHT) approaches; and the characteristic parameters of the GNSS sweep interfering signal can be efficiently estimated according to the peak position of the RWT computed in the parameter space. In order to excite the GNSS sweep interfering signal, the dechirping and notch filtering techniques have been suggested to realize the GNSS anti-interference functionality, providing satisfactory anti-interference performance for GNSS receivers, this has been further verified by the GNSS signal acquisition experiment in the interfering environment.

Radio Frequency Interference Mitigation via Nonnegative Matrix Factorization for GNSS

A radio frequency interference (RFI) mitigation approach based on nonnegative matrix factorization (NMF) for global navigation satellite systems (GNSS) signals is proposed. The proposed approach employs NMF to separate the interference from the GNSS signals, and it can be deployed in a supervised or semi-blind manner. The supervised NMF framework assumes prior knowledge about the RFI whereas its semi-blind counterpart does not require any <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> information about the RFI. Results indicate that both schemes are able to mitigate narrow and wideband RFI signals, outperforming Kalman, notch filter and wavelet-based techniques, enabling GNSS signal acquisition even in scenarios where the interference is 50 dB stronger than the GNSS signals. In addition, the proposed approach is able to mitigate multiple, different types of RFI corrupting the received GNSS signal.

Structure and Performance Analysis of Signal Acquisition and Doppler Tracking in LEO Augmented GNSS Receiver.

Due to the low signal power, the Global Navigation Satellite System (GNSS) signal is vulnerable to interference and even cannot be captured or tracked in harsh environments. As an alternative, the Low Earth Orbit (LEO) satellite has been widely used in the navigation field due to the advantages of low cost and strong signals. It is becoming a significant component of the new combined navigation system with GNSS. The combination of an LEO Doppler signal and GNSS observables can improve the positioning accuracy and high-precision positioning convergence time of the GNSS receiver. However, the GNSS signal receiving capability cannot be improved from this data fusion level. We propose a novel assisted structure where GNSS signal acquisition and Doppler tracking are assisted by LEO Doppler positioning. The receiver uses the LEO signal to achieve Doppler positioning firstly. Then, the coarse position with the GNSS navigation messages received from LEO, as well as the estimated clock information, is used to assist in the acquisition and tracking of GNSS. In this way, the GNSS receiver’s sensitivity can get the benefit from this integrated system. The paper presents the structure of the assisted receiver and analyzes the assisted GNSS signal acquisition and carrier tracking performance in detail. Simulation experiments of this assisted structure are carried out to verify its superiority of acquisition and tracking sensitivity in comparison with standalone GNSS receivers. Theoretical analysis and experimental results show that the proposed acquisition method can achieve 90% detection probability at a carrier-to-noise ratio (C/N0) of 15 dB-Hz, which is about 8 dB higher than the conventional acquisition method without assistance; the proposed tracking method can track weak signals of 5 dB-Hz, which is about 4 dB higher than the conventional method. Therefore, this novel LEO-assisted receiver has significantly improved weak signal acquisition and tracking sensitivity.

Sparse GLONASS Signal Acquisition Based on Compressive Sensing and Multiple Measurement Vectors

A sparse global navigation satellite system (GLONASS) signal acquisition method based on compressive sensing and multiple measurement vectors is proposed. The nonsparse GLONASS signal can be represented sparsely on our proposed dictionary which is designed based on the signal feature. Then, the GLONASS signal is sensed by a normalized orthogonal random matrix and acquired by the improved multiple measurement vectors acquisition algorithm. There are 10 cycles of pseudorandom codes in a navigation message, and these 10 pseudorandom codes have the same row sparse structure. So, the acquisition probability can be raised by row sparse features theoretically. A large number of simulated GLONASS signal experiments show that the acquisition probability increases with the increase in the measurement vector column dimension. Finally, the practical availability of the new method is verified by acquisition experiments with the real record GLONASS signal. The new method can reduce the storage space and energy loss of data transmission. We hope that the new method can be applied to field receivers that need to record and transmit navigation data for a long time.

Mean acquisition time analysis for GNSS parallel and hybrid search strategies

Mean acquisition time (MAT) is one of the key performance indicators for the acquisition of global navigation satellite system (GNSS) signals. Usually, there are two stages in GNSS signal acquisition, called coarse acquisition and fine acquisition. A receiver starts the coarse acquisition with relatively large code-phase and frequency steps to obtain rough code-phase and Doppler estimates. Then, it follows a fine acquisition, in which the search steps are much smaller, to obtain the more accurate code-phase and Doppler estimates to meet the tracking loop requirements, and the search space is dramatically reduced. The existing MAT models only consider the coarse acquisition stage. We present the MAT expressions in consideration of both the coarse and fine acquisition stages. Also, our models are extended versions of the existing ones. The MAT expressions for three common GNSS signal acquisition schemes are provided, including parallel code-phase search (PCS), parallel frequency search, and hybrid search. The analytical expressions are verified by Monte Carlo simulations of GPS L1 C/A signals. We show how to optimize the acquisition parameters, including detection threshold, coherent integration time, and non-coherent integration time with the metric of MAT. The models facilitate not only MAT performance evaluation but also design parameter optimization of GNSS receivers.

Constraint Sparse Maximum Correntropy Beamforming Algorithm against Impulsive Noise to Improve the Performance of GNSS Signal Acquisition

This paper presents the new constraint correntropy beamforming method to improve the performance of global navigation satellite system (GNSS) receivers. Although beamforming-based GNSS system possesses the ability of nulling interference sources, the distortions to satellite signal induced by impulsive noises are always neglected. This paper addresses the satellite navigation signal acquisition problem against impulsive noises using the constraint maximum correntropy criterion in framework of the GNSS system. In addition, in order to decrease the number of active elements for avoiding overmuch energy consumption, we introduce the L1-norm penalty equation to the list of constraints of the adaptive filter that forces the coefficients with small magnitudes to zero. From the above, we propose the norm-constraint beamforming method to satisfy the conflicting requirements between the coefficients sparsity and the performance of the satellite signal acquisition. The proposed CSMC maintains the robustness against impulsive outliers and achieve better performance in conjunction with less power consumption. An analysis of the mean square convergence properties of the proposed algorithms is presented, and the stability condition of the convergence is derived. Our simulation results demonstrate the superiority of the proposed methods.

Fast GNSS signal acquisition with Doppler frequency estimation algorithm

In both urban and indoor environments, position and navigation technologies that are based on global navigation satellite systems (GNSSs) high requirements for acquisition sensitivity of a GNSS receiver. To increase the acquisition speed and sensitivity of a GNSS receiver, a new method called improved acquisition algorithm with Doppler frequency compensation (IAADFC) is proposed to realize a long coherent integration time (CIT) acquisition algorithm to increase the sensitivity of a GNSS receiver. Its CIT can be larger than the bit length of the navigation message. Based on the parameter estimation theory, the Doppler frequency estimation algorithm (DFEA) is proposed to reduce the Doppler frequency search range (DFSR) to speed-up the acquisition process. Then, the data bit sign transition (DBST) algorithm is proposed to remove the impact of the data bit sign transition to improve acquisition sensitivity. Then, the IAADFC is discussed. Simulation results demonstrate that the IAADFC can improve the sensitivity and speed of weak GNSS signal acquisition. Finally, we provide a detailed comparison between the proposed IAADFC algorithm and the non-coherent integration (NCI) algorithm. Simulation results shown demonstrate that our IAADFC algorithm can detect weaker signals than the NCI algorithm can. This can help meet the high sensitivity requirement for indoor and outdoor seamless position and navigation service.

Energy Efficient GNSS Signal Acquisition Using Singular Value Decomposition (SVD).

A significant challenge in global navigation satellite system (GNSS) signal processing is a requirement for a very high sampling rate. The recently-emerging compressed sensing (CS) theory makes processing GNSS signals at a low sampling rate possible if the signal has a sparse representation in a certain space. Based on CS and SVD theories, an algorithm for sampling GNSS signals at a rate much lower than the Nyquist rate and reconstructing the compressed signal is proposed in this research, which is validated after the output from that process still performs signal detection using the standard fast Fourier transform (FFT) parallel frequency space search acquisition. The sparse representation of the GNSS signal is the most important precondition for CS, by constructing a rectangular Toeplitz matrix (TZ) of the transmitted signal, calculating the left singular vectors using SVD from the TZ, to achieve sparse signal representation. Next, obtaining the M-dimensional observation vectors based on the left singular vectors of the SVD, which are equivalent to the sampler operator in standard compressive sensing theory, the signal can be sampled below the Nyquist rate, and can still be reconstructed via minimization with accuracy using convex optimization. As an added value, there is a GNSS signal acquisition enhancement effect by retaining the useful signal and filtering out noise by projecting the signal into the most significant proper orthogonal modes (PODs) which are the optimal distributions of signal power. The algorithm is validated with real recorded signals, and the results show that the proposed method is effective for sampling, reconstructing intermediate frequency (IF) GNSS signals in the time discrete domain.

Processing Cost of Doppler Search in GNSS Signal Acquisition: Measuring Doppler shift in navigation satellite signals

To acquire a global navigation satellite system (GNSS) signal, the receiver must determine the Doppler offset experienced by the signal. The time and resources consumed in the Doppler search contribute to the cost and efficiency of the receiver, which is fundamentally dependent on signal processing techniques adapted for the search.

High Sensitivity and Fast Acquisition Signal Processing Techniques for GNSS Receivers: From fundamentals to state-of-the-art GNSS acquisition technologies

Higher sensitivity and faster acquisition can be two conflicting goals for a global navigation satellite system (GNSS) acquisition function, and both of the goals must be considered in the development of GNSS signal processing techniques to meet the demands for location-based services (LBSs) in GNSS-challenged environments. This article introduces the fundamentals of GNSS acquisition functions and various GNSS acquisition techniques for new GNSS signals and investigates recent acquisition techniques achieving high sensitivity and fast acquisition. It provides useful information for engineers who study state-of-the-art GNSS signal acquisition techniques and want to understand the challenges involved in improving GNSS acquisition sensitivity and acquisition time.

Myriad non‐linearity for GNSS robust signal processing

The robustness of standard correlation-based Global Navigation Satellite System (GNSS) signal processing can be significantly improved by pre-processing the input samples with a zero-memory non-linearity (ZMNL). A paradigm for the design of ZMNLs is provided by the M-estimator framework where heavy-tailed probability density functions (pdfs) are used to model the impairments affecting the input samples. The myriad non-linearity, obtained considering a Cauchy pdf, is analysed for the acquisition and tracking of GNSS signals in the presence of pulsed interference. The impact of the myriad non-linearity is theoretically characterised and Monte Carlo simulations are used to support theoretical findings. Finally, real GNSS signals collected in the presence of jamming are processed: the myriad non-linearity provides a significant performance improvement with respect to standard GNSS signal processing which is unable to acquire and track the samples affected by interference.

Re-scaling and adaptive stochastic resonance as a tool for weak GNSS signal acquisition

Weak global navigation satellite system (GNSS) signal acquisition has been a limitation for high sensitivity GPS receivers. This paper modifies the traditional acquisition algorithms and proposes a new weak GNSS signal acquisition method using re-scaling and adaptive stochastic resonance (SR). The adoption of classical SR is limited to low-frequency and periodic signals. Given that GNSS signal frequency is high and that the periodic feature of the GNSS signal is affected by the Doppler frequency shift, classical SR methods cannot be directly used to acquire GNSS signals. Therefore, the re-scaling technique is used in our study to expand its usage to high-frequency signals and adaptive control technique is used to gradually determine the Doppler shift effect in GNSS signal buried in strong noises. The effectiveness of our proposed method was verified by the simulations on GPS L1 signals. The simulation results indicate that the new algorithm based on SR can reach – 181 dBW sensitivity with a very short data length of 1 ms.

FFT Splitting for Improved FPGA-Based Acquisition of GNSS Signals

With modern global navigation satellite system (GNSS) signals, the FFT-based parallel code search acquisition must handle the frequent sign transitions due to the data or the secondary code. There is a straightforward solution to this problem, which consists in doubling the length of the FFTs, leading to a significant increase of the complexity. The authors already proposed a method to reduce the complexity without impairing the probability of detection. In particular, this led to a 50% memory reduction for an FPGA implementation. In this paper, the authors propose another approach, namely, the splitting of a large FFT into three or five smaller FFTs, providing better performances and higher flexibility. For an FPGA implementation, compared to the previously proposed approach, at the expense of a slight increase of the logic and multiplier resources, the splitting into three and five allows, respectively, a reduction of 40% and 64% of the memory, and of 25% and 37.5% of the processing time. Moreover, with the splitting into three FFTs, the algorithm is applicable for sampling frequencies up to 24.576 MHz for L5 band signals, against 21.846 MHz with the previously proposed algorithm. The algorithm is applied here to the GPS L5 and Galileo E5a, E5b, and E1 signals.

SDHT for Fast Detection of Weak GNSS Signals

Successful and fast Global Navigation Satellite System (GNSS) positioning in indoor environments can enable many location based services (LBS). However, fast indoor GNSS positioning has been one of the biggest challenges for GNSS receivers due to the huge computational cost. To detect weak GNSS signals in indoor environments, a GNSS receiver should perform numerous correlations with a longer coherent integration interval for a denser Doppler frequency search, which is computationally too expensive. For a fast and low computational weak GNSS signal detection, we propose the synthesized Doppler frequency hypothesis testing (SDHT) technique that, utilizing the test results of only sparse Doppler frequency hypotheses, can estimate the test results of entire Doppler frequency hypotheses with small computations. We provide theoretical performance analysis of the proposed technique and demonstrate that the proposed technique reduces the computational cost for weak GNSS signal acquisition significantly and achieves faster signal acquisition than conventional techniques.

Research on assessment method of intrasystem and intersystem of the global navigation satellite system

The global navigation satellite system (GNSS) has become an important space infrastructure. Following GPS and GLONASS, Europe and China have been building their own global navigation satellite system, respectively, GALILEO and Compass. In order to consolidate the leadership of GPS in the globe, United States is gradually upgrading the traditional GPS. Simultaneously, Russia is also intensively restoring full performance of GLONASS. With the advancement of international satellite navigation system, satellite navigation frequency resources are already in short supply, and the design and use of the navigation signals are more sophisticated and complex due to commercial, disaster relief and other reasons. Since there may be many navigation signals in the same basic bandwidth, the coexistence of multiple systems and the combined application make intersystem mutual interference become the focus research. Under this background, the satellite navigation system mutual interference evaluation system needs to be established urgently to meet and support the compatibility and interoperability of the GNSS system. In the paper, through the performance analysis of the GNSS signal acquisition, carrier tracking, data demodulation and code tracking, the equivalent carrier to noise ratio model based on spectrum isolation coefficient is established, and the theoretical system of the GNSS signal mutual interference is proposed according to the mechanism, and the mutual interference of GPS, GALILEO and Compass system is analyzed and assessed.

Modified compressive sensing approach for GNSS signal reception in the presence of interference

Pre-processing traditional navigation signals in global navigation satellite system (GNSS) receivers includes the conversion of an analog-to-digital sample and acquisition following the basic principle of Nyquist sampling theory. This condition inevitably increases the system computation time and cost of a modern wideband receiver. In recent years, the compressive sensing (CS) approach has been proven to effectively reduce the number of measurement samples required for digital signal acquisition systems. This method gives new potential to this modern design. In this study, a modified compressive sensing algorithm for the acquisition of a GNSS signal that is contaminated by an interfering signal is presented. The proposed method attempts to combine CS demodulation and the subspace projecting method to enhance GNSS signal acquisition performance with interference present. First, the received signal is sub-sampled and aliased from a compressive sampling process. This operation maintains the restricted isometry property (RIP) condition of the second sampling process using a Toeplitz-structured sensing matrix, which replaces a conventional random sensing matrix. The matrix ensures that distances between desired signals on the set of sparse space are not influenced by the sampling process. Next, the interference is eliminated through the orthogonal feature between the interference signal and the desired signal using the subspace projecting method. This also preserves the RIP of the projecting matrix to ensure that the original structure of the linear projection of the signal is preserved. After this, an iterative least-square method is utilized to recover the correlator output from the reception samples taken by the CS demodulator. In addition, the signal detection performance in the presence of co-channel interference using a CS demodulator is analyzed and evaluated. Finally, the relationships between signal detection probability, compressive factor and signal bandwidth are also illustrated. Several numerical results are presented to verify the theory.

Detection of buried objects using reflected GNSS signals

The use of reflected Global Navigation Satellite System (GNSS) signals for sensing the Earth has been growing rapidly in recent years. This technique is founded on the basic principle of detecting GNSS signals after they have been reflected off the Earth's surface and using them to determine the properties of the reflecting surface remotely. This is the so-called GNSS reflectometry (GNSS-R) technique. In this paper, a new application regarding the detection of metallic buried objects is analyzed and it is validated through several experimental campaigns. Although the penetration depth of GNSS signals into the ground is not optimal and depends on the soil moisture, GNSS signals can likely interact approximately with the first 10 cm of the ground and therefore can be reflected back by any metallic object buried on the first terrain layer. A very light and low-cost GNSS receiver prototype based on a software-defined radio approach was developed. This receiver can be used as a payload on board small drones or unmanned aerial systems to detect metallic objects (mines or other explosive devices). A signal processing tool based on an open-loop GNSS signal acquisition strategy was developed. The results of two experiments which show the possibility of using GNSS-R signals to detect buried metallic objects and to provide an estimate of their dimensions are discussed.

Two-Dimensional Compressed Correlator for Fast Acquisition of &lt;inline-formula&gt; &lt;tex-math notation="TeX"&gt;$\hbox{BOC}(m, n)$&lt;/tex-math&gt;&lt;/inline-formula&gt; Signals

The long spreading code and the binary offset carrier (BOC) modulation technique are used in the next-generation Global Navigation Satellite System (GNSS) to improve positioning performance and to reduce inter-GNSS interference; however, the signal acquisition process of a GNSS receiver can take more time and requires additional hardware resources than legacy Global Positioning System (GPS) receivers. This paper presents the BOC 2-D compressed correlator (TDCC) technique for the fast acquisition of the next-generation GNSS signals. In the proposed BOC-TDCC, signal power in neighboring code-phase hypotheses and Doppler frequency hypotheses can be coherently combined and tested by a single compressed correlator in the first stage, and the conventional correlator-based serial search technique is employed in the second stage to test each hypothesis combined in the first stage. The performance of the BOC-TDCC is demonstrated with numerous Monte Carlo simulations and tested with real data. The BOC-TDCC has much lower mean acquisition time (MAT) than other conventional search schemes, which demonstrates that the BOC-TDCC is an effective search scheme for next-generation GNSS signals.

Acquisition of GNSS signals in urban interference environment

In urban environment Global Navigation Satellite System (GNSS) signals are impaired by strong fading and by the presence of several potential sources of interference that can severely affect the acquisition. The work presented here evaluates the acquisition performance for the most common acquisition strategies in terms of receiver operating characteristics (ROC) and studies the impact of fading and interference on the acquisition performance. Two different interference scenarios are considered: a single interferer and a network of interferers. We present a framework to evaluate the GNSS acquisition performance with respect to all relevant system parameters that jointly considers the acquisition method, the effect of radio signal propagation conditions, and the spatial distribution of the interfering nodes.