Synthetic Aperture Radar (SAR) satellites commonly make use of onboard Global Positioning System (GPS) receivers for precise orbit and baseline determination. In view of the extreme SAR transmit power levels, interference from SAR signals may inhibit proper GPS tracking and poses a particular challenge to space missions using L-band SAR signals with frequencies adjacent to or even overlapping the GPS frequency bands. Within this study, the impact of simulated SAR signals on direct and semi-codeless GPS signal tracking is assessed in a signal simulator test bed using two commercial-off-the-shelf geodetic-grade receivers. A high robustness of GPS tracking to both adjacent-band and in-band SAR interference is obtained within the tests using representative chirp signals. For SAR signals next to or overlapping the GPS L2 band, proper tracking of the GPS L1 C/A code, GPS2 L2C, and semi-codeless L1/L2 P(Y)-code tracking is retained for interference powers up to SI{90}{db} above the natural GPS signal power. Apparently, a high level of immunity to high-power pulsed signals with repeat periods in the (sub-)ms regime is already provided by the automatic gain control of the receivers and/or a saturation of the analog-to-digital converters in the frontend that mimic an explicit pulse blanking. On the other hand, the addition of an external pulse blanking synchronized with the chirp pulses was found to be of marginal value. This unexpected result can presumably be understood by low power ``noise'' in the synthetic SAR signals that adds an additional signal outside the spectral and temporal limitations of the actual chirp signal and dominates the overall interference when simulating very high chirp signal powers.
{"title":"GNSS Interference in L-Band SAR Missions � Assessment and Mitigation","authors":"O. Montenbruck, M. Markgraf, M. Tossaint","doi":"10.33012/2019.16690","DOIUrl":"https://doi.org/10.33012/2019.16690","url":null,"abstract":"Synthetic Aperture Radar (SAR) satellites commonly make use of onboard Global Positioning System (GPS) receivers for precise orbit and baseline determination. In view of the extreme SAR transmit power levels, interference from SAR signals may inhibit proper GPS tracking and poses a particular challenge to space missions using L-band SAR signals with frequencies adjacent to or even overlapping the GPS frequency bands. Within this study, the impact of simulated SAR signals on direct and semi-codeless GPS signal tracking is assessed in a signal simulator test bed using two commercial-off-the-shelf geodetic-grade receivers. A high robustness of GPS tracking to both adjacent-band and in-band SAR interference is obtained within the tests using representative chirp signals. For SAR signals next to or overlapping the GPS L2 band, proper tracking of the GPS L1 C/A code, GPS2 L2C, and semi-codeless L1/L2 P(Y)-code tracking is retained for interference powers up to SI{90}{db} above the natural GPS signal power. Apparently, a high level of immunity to high-power pulsed signals with repeat periods in the (sub-)ms regime is already provided by the automatic gain control of the receivers and/or a saturation of the analog-to-digital converters in the frontend that mimic an explicit pulse blanking. On the other hand, the addition of an external pulse blanking synchronized with the chirp pulses was found to be of marginal value. This unexpected result can presumably be understood by low power ``noise'' in the synthetic SAR signals that adds an additional signal outside the spectral and temporal limitations of the actual chirp signal and dominates the overall interference when simulating very high chirp signal powers.","PeriodicalId":332769,"journal":{"name":"Proceedings of the 2019 International Technical Meeting of The Institute of Navigation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126400128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Long- and short-term variation of water level is critical in the Arctic as this region significantly affects the global climate and ecosystems. The water level changes are conventionally monitored by a tidal gauge. However, installing and maintaining tide gauges for continuous and seamless water level data in the Arctic is challenging due to the extreme environment. In this study, we investigate GNSS-Reflectometry (GNSS-R) as an alternative water level monitoring method in the Arctic, which measures the water levels based on remote sensing technique. Since GNSS performance at high latitudes is degraded due to satellite geometry and ionospheric effects on GNSS signals, an enhanced GNSS-R algorithm is applied, which accurately determines sea levels through enhanced spectrum analysis based on GNSS - including GPS and Galileo - multiple frequencies and statistical reliability verification. In addition, by including Galileo, the number of visible satellites is also increased that tackles another challenge of lack of available observations at high latitudes. The suggested algorithms are validated by analyzing water level changes in St. Michael, Alaska in June 2018. The water levels derived by GNSS-R based tide gauge are compared to independent data from the two neighboring NOAA’s St. Michael and Unalakleet tide gauges (ID: 9468132 and 9468333) about 1.5 km and 74 km of GNSS-R based tide gauge, respectively. As a result, a good agreement is confirmed with a high correlation coefficient of up to 0.87. In addition, from a spectral analysis, meaningful harmonic constituents, M2, K1, and O1 are founded from the sea level changes measured by GNSS-R based tide gauge. In addition, the temporal resolution of the output was significantly increased by adding the Galileo satellites. By implementing the advanced algorithms of GNSS-R, the proposed study successfully measured the highly accurate and precise water level variation in an environmentally challenging region. The experimental results show many promising applications for the Arctic GNSS-R based tide gauge.
{"title":"Monitoring Sea Level Change in Arctic using GNSS-Reflectometry","authors":"Su‐Kyung Kim, Jihye Park","doi":"10.33012/2019.16717","DOIUrl":"https://doi.org/10.33012/2019.16717","url":null,"abstract":"Long- and short-term variation of water level is critical in the Arctic as this region significantly affects the global climate and ecosystems. The water level changes are conventionally monitored by a tidal gauge. However, installing and maintaining tide gauges for continuous and seamless water level data in the Arctic is challenging due to the extreme environment. In this study, we investigate GNSS-Reflectometry (GNSS-R) as an alternative water level monitoring method in the Arctic, which measures the water levels based on remote sensing technique. Since GNSS performance at high latitudes is degraded due to satellite geometry and ionospheric effects on GNSS signals, an enhanced GNSS-R algorithm is applied, which accurately determines sea levels through enhanced spectrum analysis based on GNSS - including GPS and Galileo - multiple frequencies and statistical reliability verification. In addition, by including Galileo, the number of visible satellites is also increased that tackles another challenge of lack of available observations at high latitudes. \u0000The suggested algorithms are validated by analyzing water level changes in St. Michael, Alaska in June 2018. The water levels derived by GNSS-R based tide gauge are compared to independent data from the two neighboring NOAA’s St. Michael and Unalakleet tide gauges (ID: 9468132 and 9468333) about 1.5 km and 74 km of GNSS-R based tide gauge, respectively. As a result, a good agreement is confirmed with a high correlation coefficient of up to 0.87. In addition, from a spectral analysis, meaningful harmonic constituents, M2, K1, and O1 are founded from the sea level changes measured by GNSS-R based tide gauge. In addition, the temporal resolution of the output was significantly increased by adding the Galileo satellites. By implementing the advanced algorithms of GNSS-R, the proposed study successfully measured the highly accurate and precise water level variation in an environmentally challenging region. The experimental results show many promising applications for the Arctic GNSS-R based tide gauge.","PeriodicalId":332769,"journal":{"name":"Proceedings of the 2019 International Technical Meeting of The Institute of Navigation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126574325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Current aviation standards define a multipath error model that is valid after the smoothing filter is assumed to have converged (assuming a 100 s Hatch filter). The draft standards for dual frequency Satellite-based Augmentation Systems further specify an error model when the code has not been smoothed, and it is defined as a multiple of the converged value. In this paper, multipath and noise error bounds are derived as a function of smoothing time assuming a first order model for the code multipath and the receiver noise. These error bounds are evaluated using GPS and Galileo measurements collected in flight. The derived model appears to account well for the error reduction as a function of smoothing time. INTRODUCTION The standards for Satellite-based Augmentation Systems (SBAS) Dual Frequency Multi-constellation (DFMC) are currently being developed. With dual frequency, the residual ionospheric delay error (which is the largest contributor in single frequency) is no longer the dominant term. In particular, multipath and receiver noise is now a much more important term in the error budget. For this reason, and because of the introduction of new signals (L5 and E5a), these term is receiving more attention, and new data suggests that extrapolating L1 models to L5 and L1-L5 combination might not be sufficient [5]. This multipath and antenna group delay error model used in single frequency SBAS has been in place since 2000 [1]. This model is elevation dependent and only applies once the carrier smoothing filter has converged, which is assumed to occur after 360 s of smoothing. The current standards do not specify how the multipath error bound varies with smoothing time before convergence. The draft SBAS DFMC Minimum Operational Standards [2] (developed within EUROCAE) specifies an additional constraint: for unsmoothed code measurements, the standard deviation is ten times higher than the value at convergence. A strict application of this error model between t=0 and t = 360 s would result in very conservative error bounds, because in reality the actual errors decrease steadily as new measurements are added. In particular, it could result in significant performance losses in the presence of cycle slips. This is especially critical for environments with ionospheric scintillation (for example in low latitudes), where we expect a much higher cycle slip rate. And even if the receivers do use a less conservative multipath curve, service providers evaluating coverage would need to assume the minimum requirement, and therefore could be unable to claim availability where there might be. The goal of this paper is twofold: to derive a multipath error model that is valid before convergence, and to evaluate it using GNSS airborne measurements. In the first part, we develop three models: one corresponding to time invariant smoothing, one corresponding to time varying smoothing, and one where we start with a time varying smoothing that switches to time invariant a
当前的航空标准定义了一种多路径误差模型，该模型在平滑滤波器被假设为收敛后有效(假设是100秒的Hatch滤波器)。双频星载增强系统标准草案进一步明确了编码未平滑时的误差模型，并将其定义为收敛值的倍数。在假定码多径和接收机噪声为一阶模型的情况下，导出了多径和噪声误差边界作为平滑时间的函数。这些误差范围是使用GPS和伽利略在飞行中收集的测量值来评估的。导出的模型似乎很好地说明了作为平滑时间的函数的误差减小。星基增强系统(SBAS)双频多星座(DFMC)标准目前正在开发中。在双频条件下，残余电离层延迟误差(在单频条件下是最大的影响因子)不再占主导地位。特别是，多径和接收机噪声现在是误差预算中更重要的一个术语。由于这个原因，并且由于引入了新的信号(L5和E5a)，这些术语受到了更多的关注，新的数据表明，将L1模型外推到L5和L1-L5组合可能是不够的。这种用于单频SBAS的多径和天线群延迟误差模型自2000年以来一直存在。该模型是仰角相关的，只有在载波平滑滤波器收敛后才适用，假设这发生在360秒的平滑之后。目前的标准没有规定收敛前多径误差界如何随平滑时间变化。SBAS DFMC最低操作标准草案[2](在EUROCAE内开发)规定了一个额外的约束:对于非平滑代码测量，标准偏差比收敛值高十倍。严格应用t=0和t= 360秒之间的误差模型会导致非常保守的误差界限，因为在现实中，随着新测量的增加，实际误差会稳步下降。特别是，在出现周期滑移的情况下，它可能导致显著的性能损失。这对于电离层闪烁的环境(例如在低纬度地区)尤其重要，我们预计在那里会有更高的周期滑移率。而且，即使接收器确实使用了不那么保守的多径曲线，服务提供商评估覆盖范围时也需要假设最低要求，因此可能无法在可能存在的地方宣称可用性。本文的目标有两个:推导出收敛前有效的多径误差模型，并使用GNSS机载测量对其进行评估。在第一部分中，我们开发了三个模型:一个对应于时不变平滑，一个对应于时变平滑，一个我们从时变平滑开始，在设定的时间间隔后切换到时不变。在第二部分中，我们使用飞行中收集的GNSS数据评估了多径误差模型。多路径误差模型在本文的融合,我们将假设收敛的误差模型是由[2]中指定的公式,给出基于[1中使用的 ]: ( ) ( ) ( ) 4 4 2 2 1 5 &,, 2 2 2 1 5 L L空气议员AGVD我噪音L L f f f f+ = +−(1):0.53 (0.13)[m] . [m] . exp(/ 10[度])议员= +−(2)我们将进一步假设时间误差模型可以建模为:( ) ( ) ( )( ) ( )( ) 4 4 2 2 1 5 &,, 2 2 2 1 5 L L空气议员议员AGVD我噪音噪音我k一个k k L L f f f f+ = +−(3)k是时间步,和安培是函数,这样声音吵醒 : ( ) ( ) ( ) ( ) 0 100 360 1 0 200 360 1像素
{"title":"Development and Evaluation of Airborne Multipath Error Bounds for L1-L5","authors":"J. Blanch, T. Walter, R. E. Phelts","doi":"10.33012/2019.16735","DOIUrl":"https://doi.org/10.33012/2019.16735","url":null,"abstract":"Current aviation standards define a multipath error model that is valid after the smoothing filter is assumed to have converged (assuming a 100 s Hatch filter). The draft standards for dual frequency Satellite-based Augmentation Systems further specify an error model when the code has not been smoothed, and it is defined as a multiple of the converged value. In this paper, multipath and noise error bounds are derived as a function of smoothing time assuming a first order model for the code multipath and the receiver noise. These error bounds are evaluated using GPS and Galileo measurements collected in flight. The derived model appears to account well for the error reduction as a function of smoothing time. INTRODUCTION The standards for Satellite-based Augmentation Systems (SBAS) Dual Frequency Multi-constellation (DFMC) are currently being developed. With dual frequency, the residual ionospheric delay error (which is the largest contributor in single frequency) is no longer the dominant term. In particular, multipath and receiver noise is now a much more important term in the error budget. For this reason, and because of the introduction of new signals (L5 and E5a), these term is receiving more attention, and new data suggests that extrapolating L1 models to L5 and L1-L5 combination might not be sufficient [5]. This multipath and antenna group delay error model used in single frequency SBAS has been in place since 2000 [1]. This model is elevation dependent and only applies once the carrier smoothing filter has converged, which is assumed to occur after 360 s of smoothing. The current standards do not specify how the multipath error bound varies with smoothing time before convergence. The draft SBAS DFMC Minimum Operational Standards [2] (developed within EUROCAE) specifies an additional constraint: for unsmoothed code measurements, the standard deviation is ten times higher than the value at convergence. A strict application of this error model between t=0 and t = 360 s would result in very conservative error bounds, because in reality the actual errors decrease steadily as new measurements are added. In particular, it could result in significant performance losses in the presence of cycle slips. This is especially critical for environments with ionospheric scintillation (for example in low latitudes), where we expect a much higher cycle slip rate. And even if the receivers do use a less conservative multipath curve, service providers evaluating coverage would need to assume the minimum requirement, and therefore could be unable to claim availability where there might be. The goal of this paper is twofold: to derive a multipath error model that is valid before convergence, and to evaluate it using GNSS airborne measurements. In the first part, we develop three models: one corresponding to time invariant smoothing, one corresponding to time varying smoothing, and one where we start with a time varying smoothing that switches to time invariant a","PeriodicalId":332769,"journal":{"name":"Proceedings of the 2019 International Technical Meeting of The Institute of Navigation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132595180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Blanch, Kazuma Gunning, T. Walter, Lance de Groot, Laura Norman
This paper investigates two techniques to reduce the computational load of running multiple fault tolerant Kalman filters in order to provide integrity. These approaches are then exploited in the implementation of a solution separation integrity monitoring algorithm in a PPP Kalman filter solution. We evaluate the techniques using GNSS data collected in static and driving conditions. In our scenarios, these techniques lead to computational load reductions of at least 70% at the expense of protection level degradations of about 50%. INTRODUCTION Until recently, Precise Point Positioning (PPP) techniques [1] have mostly been used to provide high accuracy. There is a growing interest in translating the benefits of PPP to integrity and enabling its application to safety critical applications in rail, automotive, maritime, and even air navigation [2], [3], [4], [5]. In [5], we demonstrated how techniques developed for aviation applied to PPP can produce meter-level protection levels in automotive and aviation scenarios. This was achieved by implementing an integrity monitoring algorithm based on solution separation, akin to the one used to analyze Advanced RAIM performance [6], to the PPP Kalman filter solution. The principle of solution separation is to run a bank of filters, where each filter is fault tolerant to a fault or set of faults. The fault detection statistic is the difference between each of these solutions and the all-in-view solution. In addition to their optimality properties [7], solution separation algorithms offer a straightforward proof of integrity, and good performance [5]. However, they can also be expensive in terms of memory and processing time, because they require the receiver to compute a bank of filters (or a process computationally equivalent to a bank of filters, as in [11]). In the worst case, the computational load will be proportional to the number of filters. In [5] we showed that it was possible to dramatically reduce the cost of running the bank of filters: depending on the filter complexity (that is, the number of estimated states), we could run 20 to 50 additional filters for the cost of one. This was obtained by exploiting the fact that, in PPP, many of the elements in the computation (error models, corrections, etc) are common to the all filters, so that it is sufficient to compute them once for the all-in-view filter. Also, all the measurements are linearized with respect to the all-in-view position solution, which further simplifies the subset solution filters. The goal of this paper is to introduce and investigate techniques to reduce even further the cost of the solution separation for Kalman filter solutions. When the number of states is large (larger than 50), which is the expectation in a PPP multifrequency user algorithm, there are at least two steps that are computationally expensive: the determination of the Kalman gain, and the determination of the new error covariance. The first technique under inves
对于每小时10个的完整性，这意味着我们需要计算10的情况下所有一出子集的解分离统计量和10的两出子集的解分离统计量[8]。子集过滤器卡尔曼滤波方程(k)索引类似于all-in-view的:1 | 1 | 1 | 1 1 1 |ˆˆˆk k k k T k k k T T T T T T T T T x x C G W y G(3)1 1 1 | 1 | k k k k k T W T T T T C C G G(4)关于all-in-view唯一不同之处在于,我们只使用可用的测量数据的一个子集来更新状态估计。这个过程中最繁琐的步骤之一是计算如式(4)所示的协方差。可以看出，我们至少需要两个矩阵逆，其中两个矩阵都是n × n，其中n接近于100。(我们注意到几何矩阵通常很大，因此矩阵更新公式不会大大减少计算负载)。第一种方法是使用次优过滤器1| 1 * k * t *，而不是上面定义的最优过滤器。更准确地说,我们定义如下:1 1 1 | 1 | 1 | 1 |ˆˆˆk k k k T k k k k T T T T T T T T x x G W x y G(5)的矩阵1 | 1 k T T不再是由方程(4)。相反,我们试图找到一个矩阵,将导致一个合理的估计,但计算便宜。一个可能的方法是计算这个矩阵,好像之前的估计状态是由之前的all-in-view过滤器:1 1 0 1 | 1 | k k k k T T W T T T C G G(6)这个矩阵的优点是可以获得没有一个完整的矩阵求逆。我们有:1 1 0 1 | 1 | k k k k T T T T T T T C G WG G W G G WG(7)在大多数情况下,矩阵的秩k k k T T G W G G WG大大小于的秩1 0 1 | T T T C G WG。例如，在我们的PPP过滤器的个例中，这个矩阵的秩是4。我们可以写:k k k k k k T T W T G WG G G G W G(8)1 1 0 1 | 1 | k k k k T T T T T T C G WG G W G(9)使用伍德伯里矩阵身份,我们得到:1 1 0 0 1 0 0 1 | 1 | t 1 1 | t 1 1 | 1 | t 1 k k t k k k k t t t t t t t C C G W C G G G C(10)的使用这个公式可以加快计算1 | 1 k t t,因为矩阵转化通常远小于整个协方差矩阵。标准矩阵反演算法需要大约2/3n个基本运算，因此计算负荷显著减少(从近一百万到不到一百)。新的卡尔曼增益是由:1 0 0 0 t 1 | 1 | t 1 1 1 0 1 | 1 | 1 | 1 t t k t k k t k k t k t k k t k k k k t k t t t t t C G W C G k G W W G C G G W C G W(11),强调了已经计算在all-in-view过滤器。与最优滤波器相反，更新后的协方差不是由1| 1 k t t<e:1>给出的。相反，它是这样给出的:11 1| 11 1| T k k k T T T T T C I k C I k k k k k <s:2><s:2> <s:2> <e:2>(12)次优子集解:第二种方法第二种方法可以更简洁地描述。它包括对故障进行分组，这样我们就不需要运行那么多过滤器。例如，我们不是为卫星i中的故障运行一个过滤器，也不是为卫星j中的故障运行另一个过滤器，而是运行一个对i和j都容错的过滤器。这将导致较弱的解决方案位置，因此更大的保护级别。第二种方法可以被认为是次优子集解决方法，因为每个故障都由次优过滤器处理。在本文中，群是基于PRN数组成的，PRN数在几何上基本等同于随机分组。我们使用了两种类型的GNSS数据:一种是由静态接收器收集的，另一种是由安装在汽车上的接收器收集的。道路条件下收集的GNSS数据如[5]所述，并在此简要总结:•接收器:NovAtel OEM 7500•2018年3月1日1小时驾驶数据•GPS (L1 C/A-L2P半编码)，GLONASS (L1 C/A-L2P) 1hz•由NovAtel OEM729提供的正反向处理战术级IMU的真值位置。
{"title":"Reducing Computational Load in Solution Separation for Kalman Filters and an Application to PPP Integrity","authors":"J. Blanch, Kazuma Gunning, T. Walter, Lance de Groot, Laura Norman","doi":"10.33012/2019.16721","DOIUrl":"https://doi.org/10.33012/2019.16721","url":null,"abstract":"This paper investigates two techniques to reduce the computational load of running multiple fault tolerant Kalman filters in order to provide integrity. These approaches are then exploited in the implementation of a solution separation integrity monitoring algorithm in a PPP Kalman filter solution. We evaluate the techniques using GNSS data collected in static and driving conditions. In our scenarios, these techniques lead to computational load reductions of at least 70% at the expense of protection level degradations of about 50%. INTRODUCTION Until recently, Precise Point Positioning (PPP) techniques [1] have mostly been used to provide high accuracy. There is a growing interest in translating the benefits of PPP to integrity and enabling its application to safety critical applications in rail, automotive, maritime, and even air navigation [2], [3], [4], [5]. In [5], we demonstrated how techniques developed for aviation applied to PPP can produce meter-level protection levels in automotive and aviation scenarios. This was achieved by implementing an integrity monitoring algorithm based on solution separation, akin to the one used to analyze Advanced RAIM performance [6], to the PPP Kalman filter solution. The principle of solution separation is to run a bank of filters, where each filter is fault tolerant to a fault or set of faults. The fault detection statistic is the difference between each of these solutions and the all-in-view solution. In addition to their optimality properties [7], solution separation algorithms offer a straightforward proof of integrity, and good performance [5]. However, they can also be expensive in terms of memory and processing time, because they require the receiver to compute a bank of filters (or a process computationally equivalent to a bank of filters, as in [11]). In the worst case, the computational load will be proportional to the number of filters. In [5] we showed that it was possible to dramatically reduce the cost of running the bank of filters: depending on the filter complexity (that is, the number of estimated states), we could run 20 to 50 additional filters for the cost of one. This was obtained by exploiting the fact that, in PPP, many of the elements in the computation (error models, corrections, etc) are common to the all filters, so that it is sufficient to compute them once for the all-in-view filter. Also, all the measurements are linearized with respect to the all-in-view position solution, which further simplifies the subset solution filters. The goal of this paper is to introduce and investigate techniques to reduce even further the cost of the solution separation for Kalman filter solutions. When the number of states is large (larger than 50), which is the expectation in a PPP multifrequency user algorithm, there are at least two steps that are computationally expensive: the determination of the Kalman gain, and the determination of the new error covariance. The first technique under inves","PeriodicalId":332769,"journal":{"name":"Proceedings of the 2019 International Technical Meeting of The Institute of Navigation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124526202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Originally designed for military navigation, GPS has exploded into a modern tool used by government, industrial, and commercial sectors. The increasing demand for navigation has led to the operation of GPS receivers in challenging signal environments that include suburbs, forested areas, and metropolitan cities. In recent years, GPS receivers have also come under attack from commercial jamming and spoofing devices. To assure the integrity of GPS, the ability for receivers to overcome challenging signal environments must be solved. GPS vectorized signal tracking (vector tracking) has been shown to enhance receiver performance by 2 to 6 dB in poor signal environments over traditional tracking methods that rely on loop filters (scalar tracking). GLONASS, the Russian Federation’s equivalent to GPS, is another system that can be used for navigation. Today, many receivers use both GPS and GLONASS with scalar processing. Implementing the constellations into a centralized vector tracking filter gives the opportunity of enhanced navigation capability in challenging areas. In this thesis, the development and analysis of a software receiver that uses GPS and GLONASS vector tracking is performed. Specifically, the software receiver uses a centralized Vector Delay/Frequency Lock Loop (VDFLL) Kalman filter implementation to track the code and carrier dynamics of the satellite signals. Cascaded Phase Lock Loop (PLL) aiding is applied to the satellite channels to maintain carrier phase lock. Simulation results showed the software receiver’s ability to maintain accurate navigation in GPS or GLONASS jamming environments. In GPS jamming environments, GLONASS was able to maintain accurate tracking replicas of the GPS channels through the VDFLL. Experimental results from forested areas and urban canyons showed that the software receiver performed better with vector tracking than scalar tracking. Depending on the experiment, GPS and GLONASS vector tracking outperformed GPS-only vector tracking. In some environments, GLONASS became degraded, which caused noise sharing issues in the software receiver’s vector processing algorithm. ii
{"title":"A GPS and GLONASS L1 Vector Tracking Software-Defined Receiver","authors":"Tanner Watts, Scott M. Martin, D. Bevly","doi":"10.33012/2019.16686","DOIUrl":"https://doi.org/10.33012/2019.16686","url":null,"abstract":"Originally designed for military navigation, GPS has exploded into a modern tool used by government, industrial, and commercial sectors. The increasing demand for navigation has led to the operation of GPS receivers in challenging signal environments that include suburbs, forested areas, and metropolitan cities. In recent years, GPS receivers have also come under attack from commercial jamming and spoofing devices. To assure the integrity of GPS, the ability for receivers to overcome challenging signal environments must be solved. GPS vectorized signal tracking (vector tracking) has been shown to enhance receiver performance by 2 to 6 dB in poor signal environments over traditional tracking methods that rely on loop filters (scalar tracking). GLONASS, the Russian Federation’s equivalent to GPS, is another system that can be used for navigation. Today, many receivers use both GPS and GLONASS with scalar processing. Implementing the constellations into a centralized vector tracking filter gives the opportunity of enhanced navigation capability in challenging areas. In this thesis, the development and analysis of a software receiver that uses GPS and GLONASS vector tracking is performed. Specifically, the software receiver uses a centralized Vector Delay/Frequency Lock Loop (VDFLL) Kalman filter implementation to track the code and carrier dynamics of the satellite signals. Cascaded Phase Lock Loop (PLL) aiding is applied to the satellite channels to maintain carrier phase lock. Simulation results showed the software receiver’s ability to maintain accurate navigation in GPS or GLONASS jamming environments. In GPS jamming environments, GLONASS was able to maintain accurate tracking replicas of the GPS channels through the VDFLL. Experimental results from forested areas and urban canyons showed that the software receiver performed better with vector tracking than scalar tracking. Depending on the experiment, GPS and GLONASS vector tracking outperformed GPS-only vector tracking. In some environments, GLONASS became degraded, which caused noise sharing issues in the software receiver’s vector processing algorithm. ii","PeriodicalId":332769,"journal":{"name":"Proceedings of the 2019 International Technical Meeting of The Institute of Navigation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117013627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
GNSS has important applications in land vehicle positioning services. However, in special harsh scenarios such as urban canyon with strong occlusion, the stability of the GNSS signal will be significantly reduced, and the positioning result usually has a lower update rate, such as 1HZ. Therefore, GNSS can be combined with the inertial navigation system (INS) to achieve higher update rate and more stable positioning. GNSS and INS can complement each other in signal frequency and positioning accuracy, so well-positioned results can be obtained even with less expensive devices. An integration positioning algorithm that can suppress the accumulation of positioning errors in the case of GNSS outage is proposed in this paper. The algorithm is based on a technique called Partial-ZUPT and a sliding window polynomial predictor. Traditional loosely coupled integration is used in the algorithm. The experimental results show that the quadratic positional error growth can be suppressed to the first-order growth by applying the algorithm when the GNSS positioning information is invalid. In terms of positioning accuracy, the integration algorithm only shows a cumulative position error of 0.5m after about 5 seconds of the GNSS outage, which is a significant improvement compared with the RMS error of about 1.5m in the traditional loosely coupled integration algorithm.
{"title":"GNSS/INS Integration with Partial-ZUPT for Land Vehicle Navigation","authors":"Jingxuan Su, Zheng Yao, Mingquan Lu","doi":"10.33012/2019.16693","DOIUrl":"https://doi.org/10.33012/2019.16693","url":null,"abstract":"GNSS has important applications in land vehicle positioning services. However, in special harsh scenarios such as urban canyon with strong occlusion, the stability of the GNSS signal will be significantly reduced, and the positioning result usually has a lower update rate, such as 1HZ. Therefore, GNSS can be combined with the inertial navigation system (INS) to achieve higher update rate and more stable positioning. GNSS and INS can complement each other in signal frequency and positioning accuracy, so well-positioned results can be obtained even with less expensive devices. An integration positioning algorithm that can suppress the accumulation of positioning errors in the case of GNSS outage is proposed in this paper. The algorithm is based on a technique called Partial-ZUPT and a sliding window polynomial predictor. Traditional loosely coupled integration is used in the algorithm. The experimental results show that the quadratic positional error growth can be suppressed to the first-order growth by applying the algorithm when the GNSS positioning information is invalid. In terms of positioning accuracy, the integration algorithm only shows a cumulative position error of 0.5m after about 5 seconds of the GNSS outage, which is a significant improvement compared with the RMS error of about 1.5m in the traditional loosely coupled integration algorithm.","PeriodicalId":332769,"journal":{"name":"Proceedings of the 2019 International Technical Meeting of The Institute of Navigation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124737585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tengfei Da, Xueyong Xu, X. Cui, Guifeng Fan, Mingquan Lu
{"title":"A MBOC Signal Tracking Algorithm based on Split Processing Technique","authors":"Tengfei Da, Xueyong Xu, X. Cui, Guifeng Fan, Mingquan Lu","doi":"10.33012/2019.16734","DOIUrl":"https://doi.org/10.33012/2019.16734","url":null,"abstract":"","PeriodicalId":332769,"journal":{"name":"Proceedings of the 2019 International Technical Meeting of The Institute of Navigation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114234975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The magnetic field is a potentially robust and widely available source of information available for determining position on Earth. Certain measurements of the magnetic field can be obtained without the need for precise sensor attitude, facilitating position determination using only vector magnetometers in a gradiometer arrangement. A magnetic field tensor gradiometer system could provide greater spatial resolution compared to previous efforts to determine position using scalar magnetometers. This paper provides the theoretical framework for a navigation sensor capable of determining position without independent measurement of sensor attitude relative to the mapped global magnetic field.
{"title":"Magnetic Gradient Tensor Framework for Attitude-Free Position Estimation","authors":"Timothy R. Getscher, P. Frontera","doi":"10.33012/2019.16706","DOIUrl":"https://doi.org/10.33012/2019.16706","url":null,"abstract":"The magnetic field is a potentially robust and widely available source of information available for determining position on Earth. Certain measurements of the magnetic field can be obtained without the need for precise sensor attitude, facilitating position determination using only vector magnetometers in a gradiometer arrangement. A magnetic field tensor gradiometer system could provide greater spatial resolution compared to previous efforts to determine position using scalar magnetometers. This paper provides the theoretical framework for a navigation sensor capable of determining position without independent measurement of sensor attitude relative to the mapped global magnetic field.","PeriodicalId":332769,"journal":{"name":"Proceedings of the 2019 International Technical Meeting of The Institute of Navigation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129225409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sample Temporal Correlation Effect on PHMI","authors":"E. Bang, C. Milner, C. Macabiau, Philippe Estival","doi":"10.33012/2019.16684","DOIUrl":"https://doi.org/10.33012/2019.16684","url":null,"abstract":"","PeriodicalId":332769,"journal":{"name":"Proceedings of the 2019 International Technical Meeting of The Institute of Navigation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122916883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Officials at the US Department of Homeland Security have called the nation’s over-reliance on GNSS "…a single point of failure for critical infrastructure." This presentation will examine studies and real world instances of GNSS disruption that demonstrate this challenge. A policy and technology roadmap to Protect signals, Toughen receivers, and Augment signals will be presented as a frame work for ensuring national PNT resilience.
{"title":"GNSS � From a Single Point of Failure to Multiple Points of Success or How to Avoid a PNT Zombie Apocalypse","authors":"Dana A. Goward","doi":"10.33012/2019.16773","DOIUrl":"https://doi.org/10.33012/2019.16773","url":null,"abstract":"Officials at the US Department of Homeland Security have called the nation’s over-reliance on GNSS \"…a single point of failure for critical infrastructure.\" This presentation will examine studies and real world instances of GNSS disruption that demonstrate this challenge. A policy and technology roadmap to Protect signals, Toughen receivers, and Augment signals will be presented as a frame work for ensuring national PNT resilience.","PeriodicalId":332769,"journal":{"name":"Proceedings of the 2019 International Technical Meeting of The Institute of Navigation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125333429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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