<Emphasis Type="Italic">C</Emphasis>/<Emphasis Type="Italic">N</Emphasis><Subscript>0</Subscript> estimators for high-sensitivity snapshot GNSS receivers

We address the problem of estimating the carrier-to-noise ratio (C/N₀) in weak signal conditions. There are several environments, such as forested areas, indoor buildings and urban canyons, where high-sensitivity global navigation satellite system (HS-GNSS) receivers are expected to work under these reception conditions. The acquisition of weak signals from the satellites requires the use of post-detection integration (PDI) techniques to accumulate enough energy to detect them. However, due to the attenuation suffered by these signals, estimating their C/N₀ becomes a challenge. Measurements of C/N₀ are important in many applications of HS-GNSS receivers such as the determination of a detection threshold or the mitigation of near-far problems. For this reason, different techniques have been proposed in the literature to estimate the C/N₀, but they only work properly in the high C/N₀ region where the coherent integration is enough to acquire the satellites. We derive four C/N₀ estimators that are specially designed for HS-GNSS snapshot receivers and only use the output of a PDI technique to perform the estimation. We consider four PDI techniques, namely non-coherent PDI, non-quadratic non-coherent PDI, differential PDI and truncated generalized PDI and we obtain the corresponding C/N₀ estimator for each of them. Our performance analysis shows a significant advantage of the proposed estimators with respect to other C/N₀ estimators available in the literature in terms of estimation accuracy and computational resources.     

RETRACTED ARTICLE: Likelihood-based GNSS positioning using LOS/NLOS predictions from 3D mapping and pseudoranges

The accuracy of conventional global navigation satellite systems (GNSS) positioning in dense urban areas is severely degraded due to blockage and reflection of the signals by the surrounding buildings. By using 3D mapping of the buildings to aid GNSS positioning, the accuracy can be substantially improved. However, positioning performance must be balanced against computational load. Here, a likelihood-based 3D-mapping-aided (3DMA) GNSS ranging algorithm is demonstrated that enables signals predicted to be non-line-of-sight (NLOS) to contribute to the position solution without explicitly computing the additional path delay due to NLOS reception, which is computationally expensive. Likelihoods for an array of candidate positions are computed based on the difference between the measured and predicted pseudoranges. However, a skewed distribution is assumed for those signals predicted to be NLOS on the basis that the ensuing ranging errors are always positive. An overall position solution is then extracted from the likelihood surface. GNSS measurement data have been collected at several locations in both traditional and modern dense urban environments. Horizontal root-mean-square single-epoch position accuracies of 4.7, 5.6 and 6.5 m are obtained using, respectively, a Leica Viva geodetic receiver, a u-blox EVK M8T consumer-grade receiver and a Nexus 9 tablet incorporating a smartphone GNSS antenna and a GNSS chipset that outputs pseudoranges. The corresponding accuracies using single-epoch conventional GNSS positioning are 20.5, 23.0 and 28.4 m, about a factor of four larger. The 3DMA GNSS algorithms have also been implemented in real time on a Raspberry Pi 3 at a 1-Hz update rate.

     

Characterization of multipath phase rates in different multipath environments

A well-known effect of multipath propagation is multipath fading that typically causes periodic signal variations. Such signal variations may become visible in some basic GNSS observables such as the code minus carrier observable, single or double differences or in C/N ₀ time series. The frequency of these variations—also called fading frequency or multipath phase rate—strongly depends on the multipath environment, i.e. on the actual geometric conditions which can be described by the location of the satellite causing the multipath signal and the reflector location with respect to the receiving antenna. This paper gives a detailed insight on the expected multipath phase rates in different multipath environments. Different geometric conditions are analyzed, from arbitrary reflector positions to the point of dealing with the special case of ground multipath. Fading frequencies are determined by means of an empirical approach using the characteristics of real satellite passes. The approach results in distributions of multipath phase rates which are computed for a multitude of possible reflector locations and from which minimum, mean and maximum multipath phase rates can be derived.     

附加运动学约束的BDS抗差UKF导航算法

针对城市复杂环境中单一BDS导航受多路径（multipath,MP）和非视距（non-line-of-sight,NLOS）信号干扰导致精度下降的问题,提出一种附加运动学约束的抗差无迹卡尔曼滤波（unscented Kalman filter,UKF）算法。该算法基于新息向量构造等价权函数,克服了位置及接收机钟差初值不准确引起的抗差性能下降问题。同时,利用载体的近似运动方向和高程约束,进一步增强滤波解。实测车载试验结果表明,本文方法可有效抑制MP和NLOS信号的干扰,提高城市环境中的BDS导航精度。     

双极性天线在多路径效应探测中的应用

多路径效应是影响卫星定位精度和稳定性的重要因素。针对多路径环境复杂多变难以进行分析的问题,该文提出了一种利用双极性天线探测多路径的方法。详细介绍了反射信号的极性特征;通过判断信号的极性可以有效地区分直射信号和反射信号。分析了通过信号极性实现多路径探测的理论:组成双极性天线的右螺旋圆极化天线和左螺旋圆极化天线能够分别输出卫星信号中的右螺旋圆极化分量和左螺旋圆极化分量,如果两个分量的载噪比差值大于一定的门槛值,就可以推断卫星信号在传输过程中经历了多路径效应。最后通过仿真实验验证了该方法的可行性和有效性。     

LightSquared effects on estimated C/N 0, pseudoranges and positions

We present experimental results showing the impact of the proposed LightSquared (LS) Long-term Evolution (LTE) signals on both GPS and Galileo civil modulations in the L1/E1 band. The experiments were conducted in radiated mode in a large anechoic chamber. Three Galileo enabled receivers were chosen for the tests, and a state of the art GNSS signal generator was used to simulate both GPS and Galileo signals. The LTE signals were generated by an Agilent Programmable Signal Generator with a license to generate the signals according to the 3GPP LTE FDD standard. The interference impact was measured in terms of a Carrier-to-Noise power spectral density ratio (C/N ₀) degradation, in accordance with the methodology which the LS/GPS Technical Working Group (TWG) established by mandate of the FCC. A model for determining the impact of the LS signal on the considered GNSS signals is provided and is validated against experimental data. It is shown that the Galileo E1 Open Service (OS) signal is marginally more susceptible to this form of interference than the GPS L1 C/A signal due to its greater proximity to the lower edge of the L1 band. The impact of LS interference was further analyzed in terms of pseudorange and position errors. Despite its relevance for most GNSS users, this aspect was not considered by the TWG. Measurement and position domain analysis along with the study of the LS impact on the Galileo OS signals are the major contributions. The analysis confirms the results obtained by the TWG and shows that the receiver front-end plays a major role in protecting GNSS signals against RF interference. While it appears that, for now, the LS network will not be deployed, the approach taken and the results obtained herein can be readily adapted for any future terrestrial mobile network that may take the place of LS.     

Quantitative evaluation of multipath rejection capabilities of GNSS antennas

Multipath error remains the largest error source in many high precision GPS applications. To counteract this problem, solutions at both software and hardware level have been studied. Software processing by means of measurement redundancy or error predictability can be used in order to mitigate the multipath effects. In general, these techniques work properly only when the length of a reflection path exceeds that of the direct path by more than 10–20 m. Unfortunately, in most cases, reflections are generated in the area near the receiving antenna. For this reason, multipath rejection actuated at the antenna level is one of the most valid means to improve the accuracy of GPS systems. The scope of this work is twofold. First, a review of low-multipath reception requirements will be proposed for comparing different classes of high precision GNSS antennas. Based on this discussion, we introduce a quantitative evaluation of multipath rejection capabilities of a GNSS antenna. The proposed assessment technique is focused on the antenna pattern, but, in contrast to other parameters evaluating the antenna radiation characteristics, it is specifically conceived to capture the effects of multipath signals.     

GPS snow depth meter with geometry-free linear combinations of carrier phases

Multipath in global positioning system (GPS) is the interference of the microwave signals directly from satellites and those reflected before reaching the antenna, typically by the ground. Because reflected signals cause positioning errors, GPS antennas are designed to reduce such interference. Recent studies show that multipath could be utilized to infer the properties of the ground around the antenna. Here, we report one such application, i.e. a fixed GPS station used as a snow depth meter. Because the satellite moves in the sky, the excess path length of reflected waves changes at rates dependent on the antenna height. This causes quasi-periodic variations of the amplitude and phase of the received signals. Accumulation of snow reduces effective antenna heights, and we can see it by analyzing multipath signatures. Signal-to-noise ratios (SNR) are often used to analyze multipath, but they are not always available in raw GPS data files. Here, we demonstrate that the geometry-free linear combination (L4), normally used to study the ionosphere, can also be used to analyze multipath signatures. We obtained snow depth time series at a GPS station in Hokkaido, Japan, from January to April in 2009 using L4 and SNR. Then, we compared their precisions. We also discuss mechanisms responsible for the possible underestimation of the snow depth by GPS. Finally, we investigate the possibility of inferring physical conditions of the snow surface using amplitudes of multipath signatures.     

Retrieval of chlorophyll and nitrogen in Norway spruce (Picea abies L. Karst.) using imaging spectroscopy

The research evaluated the information content of spectral reflectance (laboratory and airborne data) for the estimation of needle chlorophyll (C_AB) and nitrogen (C_N) concentration in Norway spruce (Picea abies L. Karst.) needles. To identify reliable predictive models different types of spectral transformations were systematically compared regarding the accuracy of prediction. The results of the cross-validated analysis showed that C_AB can be well estimated from laboratory and canopy reflectance data. The best predictive model to estimate C_AB was achieved from laboratory spectra using continuum-removal transformed data (R²cv = 0.83 and a relative RMSEcv of 8.1%, n = 78) and from hyperspectral HyMap data using band-depth normalised spectra (R²cv = 0.90, relative RMSEcv = 2.8%, n = 13). Concerning the nitrogen concentration, we observed somewhat weaker relations, with however still acceptable accuracies (at canopy level: R²cv = 0.57, relative RMSEcv = 4.6%). The wavebands selected in the regression models to estimate C_AB were typically located in the red edge region and near the green reflectance peak. For C_N, additional wavebands related to a known protein absorption feature at 2350 nm were selected. The portion of selected wavebands attributable to known absorption features strongly depends on the type of spectral transformation applied. A method called “water removal” (WR) produced for canopy spectra the largest percentage of wavebands directly or indirectly related to known absorption features. The derived chlorophyll and nitrogen maps may support the detection and the monitoring of environmental stressors and are also important inputs to many bio-geochemical process models.     

A low-complexity algorithm for fast acquisition of weak DSSS signal in high dynamic environment

The initial acquisition of direct-sequence spread-spectrum (DSSS) signal transmitted in bursts by ground terminals at satellite-borne receiver poses an engineering challenge. We propose a low-complexity acquisition algorithm that is capable of capturing extremely weak DSSS signal in the presence of large Doppler dynamics. The algorithm uses fast Fourier transform (FFT)-based frequency-domain techniques to implement circular correlations between the received signal and the local pseudo-random noise (PRN) code, and it coherently accumulates the correlation results across multiple PRN code periods, to achieve a sufficient signal–noise ratio for reliable acquisition. We invoke another FFT procedure to perform the coherent accumulation and the fine compensation for the residual Doppler frequency offset. To highlight the advantage of the proposed algorithm, we make a complexity comparison among the proposed algorithm and two other benchmark strategies, namely the modified double block zero padding (MDBZP) and two-dimensional exhaustive search (2D-ES). It is shown that the proposed algorithm has the lowest complexity, which is particularly desirable for satellite-borne receivers where the computational resource is limited. The acquisition performance of the proposed algorithm is verified by theoretical analysis and Monte Carlo simulations and compared with that of MDBZP and 2D-ES. Moreover, we have carried out extensive tests on a hardware verification system, and we show the claimed tradeoff between performance and cost is indeed attainable with the suggested algorithm. Numerically, it is found the proposed algorithm can achieve a detection rate of 0.9 and a false alarm rate of \(10^{ - 5}\) at C/N ₀ = 29.5 dBHz over a Doppler frequency offset range of \(\left[ { - 7.5\,{\text{kHz}},7.5\,{\text{kHz}}} \right]\) in floating-point simulation, which coincides with the analytical results. The same performance is achieved at C/N ₀ = 31 dBHz in fixed-point simulation and at C/N ₀ = 31.5 dBHz on a hardware system.     

Analysis of high-frequency multipath in 1-Hz GPS kinematic solutions

High-frequency multipath would be problematic for studies at seismic or antenna dynamical frequencies as one could mistakenly interpret them as signals. A simple procedure to identify high-frequency multipath from global positioning system (GPS) time series records is presented. For this purpose, data from four GPS base stations are analyzed using spectral analyses techniques. Additional data, such as TEQC report files of L1 pseudorange multipath, are also used to analyze the high-frequency multipath and confirmation of the high-frequency multipath inferred from the phase records. Results show that this simple procedure is effective in identification of high-frequency multipath. The inferred information can aid interpretation of multipath at the GPS site, and is important for a number of reasons. For example, the information can be used to study GPS site selections and/or installations.

Navigation message demodulation for GPS receiver on-board spinning rockets

We describe a demodulation scheme for the navigation message of GPS receivers on spin-stabilized rockets. Doppler frequencies due to fast and complex dynamics, in particular high-rate spin, cause errors in carrier frequency tracking. The effects of such errors on navigation message demodulation are described through theoretical analysis and numerical simulation. A demodulation scheme that includes a frequency estimator is proposed to account for frequency tracking errors. It is demonstrated that demodulation performance is degraded 5 dB due to frequency uncertainty. Simulation results showed that a demodulator which includes maximum likelihood (ML) frequency estimator achieves near-optimal symbol error rate under these conditions. Demodulation with ML estimator achieves a bit error rate below 10^?5 for a C/N ₀?=?35 dB–Hz, for spin rates below 2.7?Hz, and a rocket radius smaller than 1 m. For the cases in which computational capabilities of the on-board GPS receiver is insufficient to implement the demodulator with ML estimator, frequency estimation methods with low complexity were also tested through numerical simulation. The proposed Kay and Quinn-Fernandes combination achieves a bit error rate below 10^?5 for a C/N ₀?=?37 dB–Hz while requiring 1/10 of processing time.     

A USRP2-based reconfigurable multi-constellation multi-frequency GNSS software receiver front end

We present a multi-constellation multi-band GNSS software receiver front end based on USRP2, a general purpose radio platform. When integrated with appropriate daughter boards, the USRP2 can be used to collect raw intermediate frequency (IF) data covering the entire GNSS family of signals. In this study, C++ class-based software receiver processing functions were developed to process the IF data for GPS L1, L2C, and L5 and GLONASS L1 and L2 signals collected by the USRP2 front end. The front end performance is evaluated against the outputs of a high end custom front end driven by the same local oscillator and two commercial receivers, all using the same real signal sources. The results show that for GPS signals, the USRP2 front end typically generates carrier-to-noise ratio (C/N ₀) at 1–3 and 1–2 dB below that of the high end front end and a NovAtel receiver, respectively. For GLONASS signals, the USRP2 C/N ₀ outputs are comparable to those of a Septentrio receiver. The carrier phase noise from the USRP2 outputs is similar to those of the benchmarking devices. These results demonstrate that the USRP2 is a suitable front end for applications, such as ionosphere scintillation studies.     

Calibrating adaptive antenna arrays for high-integrity GPS

A major challenge in using GPS guidance for aircraft final approach and landing is to reject interference that can jam reception of the GPS signals. Antenna arrays, which use space–time adaptive processing (STAP), significantly improve the signal to interference plus noise ratio, but at the possible expense of distorting the received signals, leading to timing biases that may degrade navigation performance. Rather than a sophisticated calibration approach to remove biases introduced by STAP, this paper demonstrates that a relatively compact calibration strategy can substantially reduce navigation biases, even under elevated interference conditions. Consequently, this paper develops an antenna bias calibration strategy for two classes of adaptive array algorithm and validates this method using both simulated and experimental data with operational hardware in the loop. A proof-of-concept system and an operational prototype are described, which implement the adaptive antenna algorithms and deterministic corrections. This investigation demonstrates that systems with adaptive antenna arrays can approach the accuracy and integrity requirements for automatic aircraft landing, and in particular for sea-based landing on board aircraft carriers, while simultaneously providing significant attenuation of interference. Evidence suggests that achieving these goals is possible with minimal restrictions on system hardware configuration—specifically, limitations on the permissible level of antenna anisotropy and the use of sufficient analog-to-digital converter resolution.     

Hydrocarbon micro-seepage detection from airborne hyper-spectral images by plant stress spectra based on the PROSPECT model

Hydrocarbon micro-seepage can result in vegetation spectral anomalies. Early detection of spectral anomalies in plants stressed by hydrocarbon micro-seepage could help reveal oil and gas resources. In this study, the origin of plant spectral anomalies affected by hydrocarbon micro-seepage was measured using indoor simulation experiments. We analyzed wheat samples grown in a simulated hydrocarbon micro-seepage environment in a laboratory setting. The leaf mesophyll structure (N) values of plants in oil and gas micro-seepage regions were measured according to the content of measured biochemical parameters and spectra simulated by PROSPECT, a model for extracting hydrocarbon micro-seepage information from hyper-spectral images based on plant stress spectra. Spectral reflectance was simulated with N, chlorophyll content (C_ab), water content (C_w) and dry matter content (C_m). Multivariate regression equations were established using varying gasoline volume as the dependent variable and spectral feature parameters exhibiting a high rate of change as the independent variables. We derived a regression equation with the highest correlation coefficient and applied it to airborne hyper-spectral data (CASI/SASI) in Qingyang Oilfield, where extracted information regarding hydrocarbon micro-seepage was matched with known oil-producing wells.     

An approach for developing Landsat-5 TM-based retrieval models of suspended particulate matter concentration with the assistance of MODIS

It is challenging to develop Landsat-5 TM (TM5) image-based retrieval models for estimating the suspended particulate matter concentration (C_SPM) in water when missing coincident ground C_SPM measurements. This study, with the Poyang Lake in China as a case study, proposed an approach for developing TM5-based C_SPM retrieval models with the assistance of moderate resolution imaging spectroradiometer (MODIS) images. After validation with an independent dataset, a cubic C_SPM retrieval model of 250 m MODIS red band was used to estimate the C_SPM values at 100 sampling points from the MODIS images (MODIS-based C_SPM) captured at three time periods. The MODIS-based C_SPM values at the time period with the largest C_SPM variation were combined with their coincident TM5 image reflectance for TM5-based model calibrations. The linear, quadratic, cubic, power and exponential models of MODIS-based C_SPM against TM5 single bands and their combinations were calibrated, respectively. Four best-fitting TM5-based C_SPM models were selected to retrieve the C_SPM values at 100 sampling points from the TM5 images (TM5-based C_SPM) at the other two time periods, and the coincident MODIS- and TM5-based C_SPM values were compared to assess TM5-based model performances. Model calibration results showed that the cubic and exponential models of TM5 red band (band 3) and red subtracting mid-infrared band (band 5) obtained the best fitting for estimating C_SPM from the TM5 image on 12 August 2005, and they explained 94–97% of the variation of MODIS-based C_SPM values with an estimated standard error of 6.617–8.457 mg/l. Model validations indicated that the exponential model of TM5 red band got the best result for estimating C_SPM from TM5 images when the MODIS-based C_SPM values were assumed as ground truths (correlation coefficient between MODIS- and TM5-based C_SPM values = 0.96, root mean square error = 4.60 mg/l). We concluded that the TM5-based C_SPM retrieval models could be developed with the assistance of MODIS, and the approach proposed in this study will be helpful for other researchers who also want to retrieve C_SPM from TM5 image archive but without coincident ground C_SPM measurements.     

卫星导航系统抗干扰问题研究

针对卫星导航系统的脆弱性和干扰来源,对卫星导航系统的抗干扰技术进行了研究,重点对接收机天线、射频前端、基带处理三大模块的抗干扰技术以及自适应滤波技术进行介绍和分析,对各类抗干扰技术所能抑制的干扰类型、抗干扰原理、发展状况进行阐述。分别总结了窄带干扰、宽带干扰、多径干扰适用的抗干扰技术、研究热点及存在的问题,提出了卫星导航系统抗干扰技术的发展趋势。     

Effects of azimuthal multipath asymmetry on long GPS coordinate time series

Carrier phase multipath is currently one source of unmodeled signals that may bias GPS coordinate time series significantly. We investigate the effect of simulated carrier phase multipath on time series of several sites covering the period 2002.0–2008.0 and spanning a range of observation geometries. High-, mid-, and low-latitude IGS sites are investigated as well as sites with significant signal obstructions. We examine the effect of multipath in different sectors of the sky, considering time-constant, horizontal reflectors at each of 0.1, 0.2, and 1.5 m below the antenna. The differences between a horizontally uniform multipath source are analyzed, and it is shown that positioning errors are generally larger when unmodeled carrier phase multipath is azimuthally heterogeneous. Using the adopted multipath model, height biases reach ±1 mm in case of the symmetric multipath and ±5 mm for the asymmetric multipath but this increases to being ±10 mm in the worst case. In addition to mean bias, low-frequency variations in the bias also exist, including periodic signals and leading to velocity biases of up to ±0.1 mm/year in the symmetric case and ±1 mm/year in the asymmetric case over the considered period. In contrast to the generally slowly varying observation geometry that is typically experienced, we show the effects of an abrupt change in geometry due to receiver/antenna hardware changes; in the case considered, we see changed pattern of temporal variation in the bias in addition to an instantaneous offset.     

Applying different inversion techniques to retrieve stand variables of summer barley with PROSPECT + SAIL

This study describes the retrieval of state variables (LAI, canopy chlorophyll, water and dry matter contents) for summer barley from airborne HyMap data by means of a canopy reflectance model (PROSPECT + SAIL). Three different inversion techniques were applied to explore the impact of the employed method on estimation accuracies: numerical optimization (downhill simplex method), a look-up table (LUT) and an artificial neural network (ANN) approach. By numerical optimization (Num Opt), reliable estimates were obtained for LAI and canopy chlorophyll contents (LAI × C_ab) with r² of 0.85 and 0.94 and RDP values of 1.81 and 2.65, respectively. Accuracies dropped for canopy water (LAI × C_w) and dry matter contents (LAI × C_m). Nevertheless, the range of leaf water contents (C_w) was very narrow in the studied plant material. Prediction accuracies generally decreased in the order Num Opt > LUT > ANN. This decrease in accuracy mainly resulted from an increase in offset in the obtained values, as the retrievals from the different approaches were highly correlated. The same decreasing order in accuracy was found for the difference between the measured spectra and those reconstructed from the retrieved variable values. The parallel application of the different inversion techniques to one collective data set was helpful to identify modelling uncertainties, as shortcomings of the retrieval algorithms themselves could be separated from uncertainties in model structure and parameterisation schemes.     

Considering combined or separated roughness and vegetation effects in soil moisture retrievals

For more than six years, the Soil Moisture and Ocean Salinity (SMOS) mission has provided multi angular and full-polarization brightness temperature (TB) measurements at L-band. Geophysical products such as soil moisture (SM) and vegetation optical depth at nadir (τ_nad) are retrieved by an operational algorithm using TB observations at different angles of incidence and polarizations. However, the quality of the retrievals depends on several surface effects, such as vegetation, soil roughness and texture, etc. In the microwave forward emission model used in the retrievals (L-band Microwave Emission Model, L-MEB), soil roughness is modelled with a semi-empirical equation using four main parameters (Q_r, H_r, N_rp, with p = H or V polarizations). At present, these parameters are calibrated with data provided by airborne studies and in situ measurements made at a local scale that is not necessarily representative of the large SMOS footprints (43 km on average) at global scale. In this study, we evaluate the impact of the calibrated values of N_rp and H_r on the SM and τ_nad retrievals based on SMOS TB measurements (SMOS Level 3 product) over the Soil Climate Analysis Network (SCAN) network located in North America over five years (2011–2015). In this study, Q_r was set equal to zero and we assumed that N_rH = N_rV. The retrievals were performed by varying N_rp from −1 to 2 by steps of 1 and H_r from 0 to 0.6 by steps of 0.1. At satellite scale, the results show that combining vegetation and roughness effects in a single parameter provides the best results in terms of soil moisture retrievals, as evaluated against the in situ SM data. Even though our retrieval approach was very simplified, as we did not account for pixel heterogeneity, the accuracy we obtained in the SM retrievals was almost systematically better than those of the Level 3 product. Improved results were also obtained in terms of optical depth retrievals. These new results may have key consequences in terms of calibration of roughness effects within the algorithms of the SMOS (ESA) and the SMAP (NASA) space missions.