A new algorithm for generating carrier adjusted differential GPS corrections

This paper presents a new algorithm for generating differential GPS corrections. This algorithm directly uses code and carrier observations in the measurement model of a Kalman filter, so that it is possible to use a simple stochastic observation model and to use the standard algorithm of the Kalman filter. The algorithm accounts for biases like multipath errors and instrumental delays in code observations and it shows how differential corrections are differently affected by code biases when dual or single frequency data are used.     

单频RTK动态解算的卡尔曼滤波算法研究

本文针对单频RTK提出了一种快速动态定位卡尔曼滤波算法,该方法使用C码和L1观测值,用模型改正对流层干延迟,双差大气延迟分解为测站大气天顶延迟和投影函数,与流动站位置以及站间单差模糊度组成观测方程进行卡尔曼滤波,得到单差模糊度浮点解及方差阵,通过星间求差得到双差模糊度浮点解及方差阵,结合MLAMBDA方法实时动态确定模糊度。经实测数据和IGS站数据验证该算法具有较好定位结果。     

Generation of differential GPS corrections along with performance of quality control

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Generation of differential GPS corrections along with performance of quality control

The DGPS technique can provide considerably better relative positioning accuracy than the stand-alone GPS positioning, but the improvement depends on the distance between the user and the reference station (spatial correlation), the latency of differential corrections (temporal correlation), and the quality of differential corrections. Therefore, how to correctly generate differential corrections as well as their pricision is very important to the DGPS positioning technique. This paper presents a new algorithm for generating differential GPS corrections. This algorithm directly uses code and carrier observations in the measurement model of a Kalman filter, so that it is possible to use a simple stochastic model and to use the standard algorithm of the Kalman filter. The algorithm accounts for biases like multipath errors and instrumental delays in code observations and it shows how differential corrections are differently affected by code biases when dual or single frequency data is used. In addition, the algorithm can be integrated with a real time quality control procedure. As a result, the quality of differential corrections can be guaranteed with a certain probability.     

有色噪声作用下的抗差卡尔曼滤波

根据用GPS载波相位三差观测量进行动态定位或精密导航的需求,推导了动态噪声、观测噪声为有色噪声的抗差卡尔曼滤波公式。白噪声的抗差卡尔曼滤波是有色噪声的抗差卡尔曼滤波的特例,有色噪声的抗差卡尔曼滤波为白噪声的抗差卡尔曼滤波的推广。     

精密单点定位的可靠性研究

从传统最小二乘的可靠性理论出发,推导了卡尔曼滤波观测方程和预计状态向量的可靠性理论,并与传统多余观测分量的可靠性进行比较。结果表明,两种方案的观测方程的内部可靠性不仅与观测值的精度有关,还与卫星几何结构和卫星高度角有关。卡尔曼滤波的预计状态向量的内部可靠性比观测方程的内部可靠性更易受卫星几何结构的影响。虽然两种方案的外部可靠性在收敛之后都在mm级,但伪距的收敛速度要快于载波相位。     

Double-filter model with modified Kalman filter for baseband signal pre-processing with application to ultra-tight GPS/INS integration

In federated design of ultra-tight GPS/INS integrated system, the baseband signal pre-processing is completed in a single pre-filter assigned for each channel. As the state space model of this single pre-filter includes the code tracking errors coupled with carrier tracking errors, ionospheric errors and normalized signal amplitude, the carrier tracking process may be destroyed. Also, the measurement noises are not independent any longer after passing through the code and carrier discriminators. Therefore, we propose a double-filter-based pre-filter model that distributes the carrier and code tracking into two independent filters: a conventional pre-filter, where the normalized signal amplitude is excluded from the state space and tracks only the code signal, and a 3-dimension state filter, tracking the carrier signal. The measurement information from both filters is a scalar quantity, which removes most of the noise correlation. To further improve the performance of the double-filter-based pre-filter model, we propose a modified Kalman filter algorithm. Simulation and field tests have been conducted, and the performance analysis has been done for the following configurations in a vector-tracking mode: double-filter model with modified Kalman filter, double-filter model with conventional Kalman filter and traditional single-filter model. The preliminary analysis indicates that the double-filter model with modified Kalman filter shows the best performance in tracking and navigation domains, while the traditional single-filter model shows a sub-optimal performance.     

Partial integer decorrelation: optimum trade-off between variance reduction and bias amplification

Different techniques have been developed for determining carrier phase ambiguities, ranging from float approximations to the efficient solution of the integer least square problem by the LAMBDA method. The focus so far was on double-differenced measurements. Practical implementations of the LAMBDA method lead to a residual probability of wrong fixing of the order one percent. For safety critical applications, this probability had to be reduced by eight orders of magnitude, which could be achieved by linear multi-frequency code–carrier combinations. Scenarios with single or no differences include biases due to orbit errors, satellite clock offsets, as well as residual code and phase biases. For this case, a linear combination of Galileo E1 and E5 code and carrier phase measurements with a wavelength of 3.285 m and a noise level of a few centimeters is derived. This ionosphere-free combination preserves the orbit and clock errors, and suppresses the E1 code multipath by 12.6 dB. Since integer decorrelation transformations, as used in the LAMBDA method, inflate biases, the number of such transformations must be limited, and applied in a judicious order. With a Galileo type constellation, this leads to a vertical standard deviation of ca. 20 cm, while keeping the probability of wrong fixing extremely low for code biases of 10 cm, and phase biases of 0.1 cycle, combined in a worst case.     

An all-pass filter for compensation of ionospheric dispersion effects on wideband GNSS signals

Compared with the traditional GPS L1 C/A BPSK-R(1) signal, wideband global navigation satellite system (GNSS) signals suffer more severe distortion due to ionospheric dispersion. Ionospheric dispersion inevitably introduces additional errors in pseudorange and carrier phase observations that cannot be readily eliminated by traditional methods. Researchers have reported power losses, waveform ripples, correlation peak asymmetries, and carrier phase shifts caused by ionospheric dispersion. We analyze the code tracking bias induced by ionospheric dispersion and propose an efficient all-pass filter to compensate the corresponding nonlinear group delay over the signal bandwidth. The filter is constructed in a cascaded biquad form based on the estimated total electron content (TEC). The effects of TEC accuracy, filter order, and fraction parameter on the filter fitting error are explored. Taking the AltBOC(15,10) signal as an example, we compare the time domain signal waveforms, correlation peaks, code tracking biases, and carrier phase biases with and without this all-pass filter and demonstrate that the proposed delay-equalization all-pass filter is a potential solution to ionospheric dispersion compensation and mitigation of observation biases for wideband GNSS signals.     

A two-step ionospheric modeling algorithm considering the impact of GLONASS pseudo-range inter-channel biases

The Global Navigation Satellite System presents a plausible and cost-effective way of computing the total electron content (TEC). But TEC estimated value could be seriously affected by the differential code biases (DCB) of frequency-dependent satellites and receivers. Unlike GPS and other satellite systems, GLONASS adopts a frequency-division multiplexing access mode to distinguish different satellites. This strategy leads to different wavelengths and inter-frequency biases (IFBs) for both pseudo-range and carrier phase observations, whose impacts are rarely considered in ionospheric modeling. We obtained observations from four groups of co-stations to analyze the characteristics of the GLONASS receiver P1P2 pseudo-range IFB with a double-difference method. The results showed that the GLONASS P1P2 pseudo-range IFB remained stable for a period of time and could catch up to several meters, which cannot be absorbed by the receiver DCB during ionospheric modeling. Given the characteristics of the GLONASS P1P2 pseudo-range IFB, we proposed a two-step ionosphere modeling method with the priori IFB information. The experimental analysis showed that the new algorithm can effectively eliminate the adverse effects on ionospheric model and hardware delay parameters estimation in different space environments. During high solar activity period, compared to the traditional GPS + GLONASS modeling algorithm, the absolute average deviation of TEC decreased from 2.17 to 2.07 TECu (TEC unit); simultaneously, the average RMS of GPS satellite DCB decreased from 0.225 to 0.219 ns, and the average deviation of GLONASS satellite DCB decreased from 0.253 to 0.113 ns with a great improvement in over 55%.     

Group delay variations of GPS transmitting and receiving antennas

GPS code pseudorange measurements exhibit group delay variations at the transmitting and the receiving antenna. We calibrated C1 and P2 delay variations with respect to dual-frequency carrier phase observations and obtained nadir-dependent corrections for 32 satellites of the GPS constellation in early 2015 as well as elevation-dependent corrections for 13 receiving antenna models. The combined delay variations reach up to 1.0 m (3.3 ns) in the ionosphere-free linear combination for specific pairs of satellite and receiving antennas. Applying these corrections to the code measurements improves code/carrier single-frequency precise point positioning, ambiguity fixing based on the Melbourne–Wübbena linear combination, and determination of ionospheric total electron content. It also affects fractional cycle biases and differential code biases.     

北斗卫星伪距多路径系统偏差的修正方法及其对单频PPP的影响分析

北斗伪距观测值存在特有的多路径系统性偏差,偏差的数量级达到几个分米到米。该系统偏差可分为两类:一类是IGSO/MEO卫星随高度角变化的伪距系统性偏差;另一类是GEO卫星(高度角仅微小变化)明显的伪距系统性偏差。系统性的伪距偏差导致GEO卫星MP序列的标准偏差较大,本文针对GEO卫星伪距偏差问题提出了一种基于卡尔曼滤波的修正方法,修正后的GEO卫星MP序列的标准偏差下降了10%~16%。基于伪距相位组合的单频PPP技术的伪距权重较大,会受到北斗伪距偏差的影响,分析表明该系统性偏差将导致单频PPP定位结果高程方向产生约1m的偏差。对GEO伪距偏差采用提出的卡尔曼滤波修正方法进行修正,并应用Wanninger和Beer的高度角模型消除IGSO/MEO观测值伪距偏差,本文对修正后的单频精密单点定位精度进行了分析。4个multi-GNSS experiment(MGEX)站10d观测数据的分析结果表明:仅改正和卫星多路径误差,高程方向定位结果精度可改善65%左右;采用本文方法对GEO卫星的多路径修正后,该方向定位结果精度改善比例将进一步提高至75%左右。     

精密单点定位不等精度观测值的RKF研究

推导了精密单点定位含有粗差观测数据的M-LS滤波原理,对等价权阵采用三段降权函数实现抗差。从新息和残差的协方差关系出发,利用对粗差敏感的残差标准差作为抗差因子。通过迭代减弱卫星间载波残差及其抗差因子的相关性。针对载波和伪距观测值不等观测精度和不相关性,采用双抗差因子实现静态抗差卡尔曼滤波（robust Kalman filtering,RKF）。采用标准卡尔曼滤波、基于新息RKF、基于残差的增益矩阵双抗差因子RKF、基于残差的等价权阵双抗差因子RKF等4种模型,分别对一组实测数据解算分析。结果表明,基于新息RKF对精度较高的载波粗差不敏感;基于残差的增益矩阵RKF对载波较小的粗差抗差效果较差,且发生粗差历元时刻的状态参数与真值偏差较大;而基于残差构造的等价权阵双抗差因子RKF可以非常精确和高效地实现抗差,单个卫星粗差对测站位置参数影响小于1 mm。     

Carrier phase-based integrity monitoring for high-accuracy positioning

Pseudorange-based integrity monitoring, for example receiver autonomous integrity monitoring (RAIM), has been investigated for many years and is used in various applications such as non-precision approach phase of flight. However, for high-accuracy applications, carrier phase-based RAIM (CRAIM), an extension of pseudorange-based RAIM (PRAIM) must be used. Existing CRAIM algorithms are a direct extension of PRAIM in which the carrier phase ambiguities are estimated together with the estimation of the position solution. The main issues with the existing algorithms are reliability and robustness, which are dominated by the correctness of the ambiguity resolution, ambiguity validation and error sources such as multipath, cycle slips and noise correlation. This paper proposes a new carrier phase-based integrity monitoring algorithm for high-accuracy positioning, using a Kalman filter. The ambiguities are estimated together with other states in the Kalman filter. The double differenced pseudorange, widelane and carrier phase observations are used as measurements in the Kalman filter. This configuration makes the positioning solution both robust and reliable. The integrity monitoring is based on a number of test statistics and error propagation for the determination of the protection levels. The measurement noise and covariance matrices in the Kalman filter are used to account for the correlation due to differencing of measurements and in the construction of the test statistics. The coefficient used to project the test statistic to the position domain is derived and the synthesis of correlated noise errors is used to determine the protection level. Results from four cases based on limited real data injected with simulated cycle slips show that residual cycle slips have a negative impact on positioning accuracy and that the integrity monitoring algorithm proposed can be effective in detecting and isolating such occurrences if their effects violate the integrity requirements. The CRAIM algorithm proposed is suitable for use within Kalman filter-based integrated navigation systems.

TJS-2 geostationary satellite orbit determination using onboard GPS measurements

This study analyzes the quality of onboard data of tracking signals from GPS satellites on the far side of the earth and determines the orbit of the geostationary satellite using code and carrier phase observations with 30-h and 3-day orbit arc length. According to the analysis results, the onboard receiver can track 6–8 GPS satellites, and the minimum and maximum carrier to noise spectral densities were 24 and 45 dB-Hz, respectively. For a GPS receiver on a high-altitude platform above the navigation constellations, the blocking of the earth and a weak signal strength usually cause a piece-wise GPS signal tracking and an increase in the number of ambiguity parameters. Individual GPS satellites may be continuously tracked for as little as several minutes and as long as 3 h. Moreover, considering the negative sign of elevation angles reflects the fact that GPS satellites are tracked below the receiver in the study. GPS satellites appear mainly in the elevation angle range of ??53° to ??83°, and dilution of precision values could reach ten or one hundred and more. Also, it is observed that when a signal suffers from atmospheric refraction, other GPS signals tracked simultaneously by the receiver experience strong systematic errors in the code observations. Based on single-frequency code and carrier phase measurements, the mean 3D root mean square (RMS) value of the overlap comparisons between 30-h orbit determination arcs is 2.14 m. However, we found that there were also some biases in the carrier phase residuals, which contributed to poor orbit accuracy. To eliminate the effects of the biases, we established a correction sequence for each GPS satellite. After corrections, the mean 3D RMS was reduced to 0.99 m, representing a 53% improvement.     

基于模糊逻辑的自适应强跟踪卡尔曼滤波在GPS定位中的应用

当载体速度频繁发生突变时,针对卡尔曼滤波在GPS定位解算中对系统模型依赖性强、鲁棒性差的问题,提出了一种基于模糊逻辑的自适应强跟踪卡尔曼滤波算法。该算法主要利用模糊逻辑自适应控制器监测系统输出的残差均值,并根据模糊规则动态调整弱化因子,从而对强跟踪滤波器中次优渐消因子进行自适应调整,来实现抑制载体突变影响。仿真结果表明,该算法在载体突变的跟踪精度高于扩展卡尔曼滤波和强跟踪卡尔曼滤,其稳定性也有所提高。      

Spatially convergent GPS kinematic positioning

It is a known fact that obtaining accurate GPS carrier-phase measurements involves fixed, unknown whole-cycle ambiguity parameters. As the use of cosine functions to eliminate any double-difference integer ambiguities causes spatial ambiguity problems, both reasonably approximated positions and wavelength-dependent convergence ranges are of the utmost importance. Differential GPS-based position solutions are first smoothed to create a polynomial trajectory, leading to less variable position approximations. Long-wavelength wide-lane phase combinations will then be utilized to facilitate convergent GPS positioning, on a stage-by-stage basis. Although double-difference ionospheric path delays are often interpreted as nuisance parameters, they can be obtained when the respective cosines of the original L1 and L2 carrier phases undergo a simultaneous least-squares estimation. In particular, quadratic forms of the estimated phase residuals will be linked with hypothesis testing to allow for a meaningful statistical inference. Some low-dynamics experiments are then performed to prove the feasibility of the proposed hierarchical positioning concept. Electronic Publication     

Hybrid derivative-free extended Kalman filter for unknown lever arm estimation in tightly coupled DGPS/INS integration

Differential carrier phase observations from GPS (Global Positioning System) integrated with high-rate sensor measurements, such as those from an inertial navigation system (INS) or an inertial measurement unit (IMU), in a tightly coupled approach can guarantee continuous and precise geo-location information by bridging short outages in GPS and providing a solution even when less than four satellites are visible. However, to be efficient, the integration requires precise knowledge of the lever arm, i.e. the position vector of the GPS antenna relative to the IMU. A previously determined lever arm by direct measurement is not always available in real applications; therefore, an efficient automatic estimation method can be very useful. We propose a new hybrid derivative-free extended Kalman filter for the estimation of the unknown lever arm in tightly coupled GPS/INS integration. The new approach takes advantage of both the linear time propagation of the Kalman filter and the nonlinear measurement propagation of the derivative-free extended Kalman filter. Compared to the unscented Kalman filter, which in recent years is typically used as a superior alternative to the extended Kalman filter for nonlinear estimation, the virtue of the new Kalman filter is equal estimation accuracy at a significantly reduced computational burden. The performance of the new lever arm estimation method is assessed with simulated and real data. Simulations show that the proposed technique can estimate the unknown lever arm correctly provided that maneuvers with attitude changes are performed during initialization. Field test results confirm the effectiveness of the new method.     

On-the-fly GPS-based attitude determination using single- and double-differenced carrier phase measurements

Carrier phase measurements are primary observations for GPS attitude determination. Although the satellite-related errors can be virtually eliminated by forming single differences, the baseline-related errors such as line biases are still present in the single-differenced carrier phase measurements. It is, therefore, difficult to resolve the single-differenced integer ambiguities due to the line biases. By forming double differences, the line biases of the single-differenced carrier phase measurements can be effectively removed. However, the main disadvantages of this method lie in the fact that the double-differenced measurements are mathematically correlated and consequently the attitude obtained from the double differences is noisy. This paper presents a new algorithm through which both single and double differences are used simultaneously to resolve these problems in real-time. The solution of the integer ambiguities can be obtained by searching for the most likely grid point in the attitude domain that is independent of the correlation with the double differences. Next, the line biases and corresponding single difference integer ambiguities can be resolved on the fly by using the noisy attitude solution obtained from the previous double difference procedure. In addition, the relationship between the physical signal path difference and the line bias is formed. A new method is also applied to derive the attitude angles through finding the optimal solution of the attitude matrix element. The proposed new procedure is validated using ground and flight tests. Results have demonstrated that the new algorithm is effective and can satisfy the requirement of real-time applications.     

基于GPS的新测姿算法

GPS载波相位测姿过程中，以往整周模糊度解决法难以实现运载体的实时测姿要求，针对这个问题，提出用超短基线首先解决初始粗定姿，然后把短基线天线的载波相位测量值和初始定姿值用卡尔曼滤波解算，最终求得载体的精确姿态值。