Ultra-tight Integration Research Articles

Non-consecutive GNSS signal tracking-based ultra-tight integration system of GNSS/INS for smart devices

Non-consecutive GNSS signal tracking-based ultra-tight integration system of GNSS/INS for smart devices

Code phase tracking error based autonomous integrity monitoring for GNSS/INS ultra-tightly integrated system

The ultra-tight integration of GNSS (Global Navigation Satellite System) and INS (Inertial Navigation System) may suffer from faults in GNSS, INS and integration filter. Both the faults occurred at the current epoch and at previous epochs affect the position solution deviation of ultra-tight integration at the current epoch, and the effect is reflected in GNSS code phase tracking errors. In this paper, a new autonomous integrity monitoring algorithm is proposed for the federated GNSS/INS ultra-tight integrations in which the code phases of local GNSS signal replicas for GNSS signal tracking are completely derived from the integrated navigation solution. In the proposed algorithm, GNSS code phase tracking errors are employed to construct the test statistics for fault detection through a MHSS (Multiple Hypothesis Solution Separation) method improved from the classical MHSS used in ARAIM (Advanced Receiver Autonomous Integrity Monitoring). With the improved MHSS, the proposed algorithm can account for GNSS nominal biases, multiple GNSS faults and the faults in INS and integration filter. The protection levels under multiple hypothesis are also derived. A semi-physical simulation of the federated ultra-tight integration of GPS (Global Positioning System) and INS in airplane approaching case and a vehicle-based field test of the federated ultra-tight integration of GPS, Galileo and INS are conducted to validate the proposed algorithm. The experiments show that the designed fault detection can effectively detect the occurred faults and the derived protection levels can correctly bound the caused position solution error.

Performance Analysis and Architectures for a MEMS-SINS/GPS Ultratight Integration System

In order to analyze the performance of strapdown inertial navigation system/global position system (SINS/GPS) ultratight integration system with low-precision microelectromechanical system (MEMS) under challenging environments, a new MEMS-SINS/GPS ultratight integration scheme is designed. The time-space difference carrier phase velocity (TSDCP-v) is used to assist the carrier tracking loop, the measurement model including nonlinear term is established, and the corresponding filtering algorithm is designed. A simulation and verification platform is established to analyze and verify the performance of the MEMS-SINS/GPS ultratight integration system designed in this paper. Compared with the SINS/GPS tight integration navigation system, the MEMS-SINS/GPS ultratight integration system has higher dynamic performance, anti-interference capability, and navigation performance. At the same time, the MEMS-SINS/GPS ultratight integration system improves the carrier tracking performance of SINS-assisted GPS ultratight integration system when using low-precision MEMS and in high dynamics, strong interference environments.

A Novel Linear Model Based on Code Approximation for GNSS/INS Ultra-Tight Integration System.

The superiority of a global navigation satellite system (GNSS)/inertial navigation system (INS) ultra-tight integration navigation system has been widely verified. For those systems with centralized structure based on coherent-accumulation measurements (I/Q), the conversion from I/Q signals to navigation information is implemented by an observation equation. As a result, the model is highly complex and nonlinear, exerting essential influence on system performance. Based on the analysis of previous studies, a novel model and its linearization method are proposed, aiming at the integrity, stability and implicit nonlinear factors. Unlike the one-order precision in the common Jacobian matrix, two-order components are partly reserved in this model, which makes it possible for higher positioning accuracy and better convergence. For the positioning errors caused by ignoring code-loop deviation, a method to approximate code-phase is proposed without introducing new measurements. Consequently, the effect of code error can be significantly reduced, especially when the tracking loops are unstable. In the end, using real-sampled satellite signals, semi-physical experiments are carried out and the effectiveness and superiority of new methods are proved.

A New Efficient Filtering Model for GPS/SINS Ultratight Integration System

Global Positioning System (GPS) and strap-down inertial navigation system (SINS) are recognized as highly complementary and widely employed in the community. The GPS has the advantage of providing precise navigation solutions without divergence, but the GPS signals might be blocked and attenuated. The SINS is a totally self-contained navigation system which is hardly disturbed. The GPS/SINS integration system could utilize the advantages of both the GPS and SINS and provide more reliable navigation solutions. According to the data fusion strategies, the GPS/SINS integrated system could be divided into three different modes: loose, tight, and ultratight integration (LI, TI, and UTC). In the loose integration mode, position and velocity difference from the GPS and SINS are employed to compose measurement vector, in which the vector dimension has nothing to do with the amount of the available satellites. However, in the tight and ultratight modes, difference of pseudoranges and pseudorange rates from the GPS and SINS are employed to compose the measurement vector, in which the measurement vector dimension increases with the amount of available satellites. In addition, compared with the loose integration mode, clock bias and drift are included in the integration state model. The two characteristics magnify the computation load of the tight and ultratight modes. In this paper, a new efficient filter model was proposed and evaluated. Two schemes were included in this design for reducing the computation load. Firstly, a difference between pseudorange measurements was determined, by which clock bias and drift were excluded from the integration state model. This step reduced the dimension of the state vector. Secondly, the integration filter was divided into two subfilters: pseudorange subfilter and pseudorange rate subfilter. A federated filter was utilized to estimate the state errors optimally. In the second step, the two subfilters could run in parallel and the measurement vector was divided into two subvectors with lower dimension. A simulation implemented in MATLAB software was conducted to evaluate the performance of the new efficient integration method in UTC. The simulation results showed that the method could reduce the computation load with the navigation solutions almost unchanged.

An Innovative High-Precision Scheme for a GPS/MEMS-SINS Ultra-Tight Integrated System.

The Doppler-assisted error provided by a low-precision microelectromechanical system (MEMS) strapdown inertial navigation system (SINS) increases rapidly. Therefore, the bandwidth of the tracking loop for a global positioning system (GPS)/MEMS-SINS ultra-tight integration system is too narrow to track Doppler shift. GPS measurement error is correlated with the MEMS-SINS velocity error when the Doppler-assisted error exists, leading to tracking loop lock loss. The estimated precision of the integrated Kalman filter (IKF) also decreases. Even the integrated system becomes unstable. To solve this problem, an innovative GPS/MEMS-SINS ultra-tight integration scheme based on using high-precision carrier phase measurements as the IKF measurements is proposed in this study. By assisting the tracking loop with time-differenced carrier phase (TDCP) velocity, the carrier loop noise bandwidth and code correlator spacing are reduced. The tracking accuracies of the carrier and code are increased. The navigation accuracy of GPS/MEMS-SINS ultra-tight integration is further improved.

GNSS/MEMS IMU ultra‐tightly integrated navigation system based on dual‐loop NCO control method and cascaded channel filters

A coherent scheme of federated architecture for the ultra-tight integration of global navigation satellite system (GNSS) and MEMS (micro-electro-mechanical system) inertial measurement unit (IMU) is presented. Inside the receiver baseband, both the controls for code numerically controlled oscillator (NCO) and carrier NCO are designed. They are each composed of two parts, one part is derived from the navigation solutions of outer loop, and the other part is given on the basis of the channel pre-filter outputs from inner loop. Each tacking channel has two filters of cascaded structure, one is the traditional pre-filter which is used to achieve GNSS signal tracking errors, and the second one is an extractor which is constructed to extract navigation solution derivation errors from the designed NCO controls and the signal tracking errors. For the ultra-tight integration navigation filter, the receiver clock residual error model after compensating the receiver clock drift is derived in detail. Finally, semi-physical simulation environment of the proposed ultra-tight integration scheme is built and closed-loop experiment under high dynamics scenario is put forward. The simulation results show that the proposed integration scheme can stably and robustly track the GNSS signals, and can achieve accurate navigation solutions even in harsh cases.

A jamming tolerant BeiDou combined B1/B2 vector tracking algorithm for ultra-tightly coupled GNSS/INS systems

All Global Navigation Satellite System (GNSS) signals could be easily disturbed by intentional jamming in hostile environment. To deal with these threats, ultra-tight GNSS/INS integration has been developed. However, most of them have focused on the single-frequency system. This paper proposes a novel vector tracking strategy, which uses pre-filters to combine both BeiDou B1 and B2 signals tracking simultaneously and then feed the tracking for the ultra-tightly coupled GNSS/INS systems. The Doppler shift relationship between B1 signal and B2 signal has been analyzed to combine the replica carrier signals tracking of different bands. Moreover, the inherent relationships between INS states and replica code phase and carrier frequency biases have been described based on construction of the correlation model. Finally, semi-physical simulation results indicate that the proposed ultra-tight integration approach based on BeiDou combined B1/B2 vector tracking algorithm can significantly improve the receiver's tracking ability and navigation performance comparing with the conventional ultra-tight integration approach under the signal jamming environments.

Sample-Wise Aiding in GPS/INS Ultra-Tight Integration for High-Dynamic, High-Precision Tracking.

By aiding GPS receiver tracking loops with INS estimates of signal dynamics, GPS/INS ultra-tight coupling can improve the navigation performance in challenging environments. Traditionally the INS data are injected into the loops once every loop update interval, which limits the levels of dynamics accommodated. This paper presents a sample-wise aiding method, which interpolates the aiding Doppler into each digital sample of the local signal to further eliminate the dynamic errors. The relationship between the tracking error and the aiding rate is derived analytically. Moreover, the effects of sample-wise aiding using linear and spline interpolations are simulated and compared with traditional aiding under different INS data update rates. Finally, extensive tests based on a digital IF (intermediate frequency) signal simulator and a software receiver validate the theoretical equations and demonstrate that the dynamic stress error can be significantly reduced by sample-wise aiding.

Time–space difference based GPS/SINS ultra-tight integrated navigation method

Presently there are several shortcomings in Global Positioning System/Strapdown Inertial Navigation System (GPS/SINS) ultra-tight integrated navigation system, for example, presences of modeling errors, heavy computation load and residual time errors, etc. To address these problems, this paper proposes a time–space difference based ultra-tight integrated navigation method. This system carries out difference in time and space which eliminates the troposphere delay, ionosphere delay, satellite and receiver clock error, reduces the system complexity and decreases the adverse impact (frequently changing weather and the low accuracy clocks of receiver and satellites) on the system. In this way the system improves the estimation accuracy and anti-jamming ability. Finally, theoretical analysis and simulation results substantiate that the proposed system has the practicability and superiority over the contemporary ultra-tight integration schemes.

Performance assessment of a low‐cost inertial measurement unit based ultra‐tight global navigation satellite system/inertial navigation system integration for high dynamic applications

Owing to large Doppler shifts, the signal of global navigation satellite system is difficult to be acquired and tracked by a receiver for high dynamic vehicles, such as missiles, aircrafts and spacecrafts. Hence, the inertial navigation system is usually used to aid the acquisition and tracking. Compared with the traditional scale tracking, the vector tracking has better performances in the navigation robustness and the immunity to interferences. Although the vector tracking aided by a low-cost inertial measurement unit (IMU) is not as good as the one aided by high-grade IMU in the tracking performance and stability, the low-cost IMU based vector tracking loop has lower price, smaller size and lighter weight. Hence, it is valuable to reduce the expense of ultra-tight integration system. In this paper, an ultra-tight integration system using the low-cost IMU based vector tracking is proposed to achieve the vector tracking and navigation for high dynamic applications. As the critical factor in the ultra-tight integration, the Doppler frequency shift is estimated and compensated to achieve the acquisition and tracking of every satellite. Then, a vector tracking Kalman filter is designed to implement the vector tracking and integrated navigation. To verify the effectiveness of the ultra-tight integration, an experiment system is built and a high dynamic scenario is simulated. The results prove that the designed ultra-tight integration system has perfect tracking and navigation performances for high dynamic applications.

Performance analysis of a federated ultra-tight global positioning system/inertial navigation system integration algorithm in high dynamic environments

The Doppler frequency changes rapidly due to high dynamics of vehicle, which leads to the loose lock and even the abnormal performance of global positioning system (GPS) receiver. To solve this problem, a federated ultra-tight integration algorithm based on pre-filters is proposed to optimal estimate both receiver tracking control commands and inertial navigation system (INS) navigation solutions. Firstly, the INS error model and GPS receiver tracking loop structure are built to present the fundamental architecture of the proposed ultra-tightly coupled system. Meanwhile, in order to reduce the load of the integrated filter, the pre-filters are incorporated to the ultra-tightly coupled system, and the state variables are fed into the integrated Kalman filter. Secondly, the intrinsic relevance between the phase and frequency biases of replica signals and INS states is analyzed to accomplish the deep fusion of INS and tracking loop. Finally, semi-physical simulations are performed by using a GPS signal simulator to generate signals of two high dynamic trajectories. The experimental results indicate that the proposed ultra-tight integration algorithm can achieve a good performance on reliable positioning and robust tracking in high dynamic environments, compared with the conventional approaches such as tightly coupled integration strategy and third-order phase-locked loops.

Performance Improvement of Receivers Based on Ultra-Tight Integration in GNSS-Challenged Environments

Ultra-tight integration was first proposed by Abbott in 2003 with the purpose of integrating a global navigation satellite system (GNSS) and an inertial navigation system (INS). This technology can improve the tracking performances of a receiver by reconfiguring the tracking loops in GNSS-challenged environments. In this paper, the models of all error sources known to date in the phase lock loops (PLLs) of a standard receiver and an ultra-tightly integrated GNSS/INS receiver are built, respectively. Based on these models, the tracking performances of the two receivers are compared to verify the improvement due to the ultra-tight integration. Meanwhile, the PLL error distributions of the two receivers are also depicted to analyze the error changes of the tracking loops. These results show that the tracking error is significantly reduced in the ultra-tightly integrated GNSS/INS receiver since the receiver's dynamics are estimated and compensated by an INS. Moreover, the mathematical relationship between the tracking performances of the ultra-tightly integrated GNSS/INS receiver and the quality of the selected inertial measurement unit (IMU) is derived from the error models and proved by the error comparisons of four ultra-tightly integrated GNSS/INS receivers aided by different grade IMUs.

Performance enhancement for ultra-tight GPS/INS integration using a fuzzy adaptive strong tracking unscented Kalman filter

This paper conducts performance evaluation for the ultra-tight integration of Global positioning system (GPS) and inertial navigation system (INS) by use of the fuzzy adaptive strong tracking unscented Kalman filter (FASTUKF). An ultra-tight GPS/INS integration architecture involves fusion of the in-phase and quadrature components from the correlator of the GPS receiver with the INS data. These two components are highly nonlinearly related to the navigation states. The strong tracking unscented Kalman filter (STUKF) is based on the combination of an unscented Kalman filter (UKF) and strong tracking algorithm (STA) to perform the parameter adaptation task for various dynamic characteristics. The STA is basically a nonlinear smoother algorithm that employs suboptimal multiple fading factors, in which the softening factors are involved. In order to resolve the shortcoming in a traditional approach for selecting the softening factor through personal experience or computer simulation, the Fuzzy Logic Adaptive System (FLAS) is incorporated for determining the softening factor, leading to the FASTUKF. Two examples are provided for illustrating the effectiveness of the design and demonstrating effective improvement in navigation estimation accuracy and, therefore, the proposed FASTUKF algorithm can be considered as an alternative approach for designing the ultra tightly coupled GPS/INS integrated navigation system.

Nonlinear Filtering with IMM Algorithm for Ultra-Tight GPS/INS Integration

Abstract This paper conducts a performance evaluation for the ultra-tight integration of a Global positioning system (GPS) and an inertial navigation system (INS), using nonlinear filtering approaches with an interacting multiple model (IMM) algorithm. An ultra-tight GPS/INS architecture involves the integration of in-phase and quadrature components from the correlator of a GPS receiver with INS data. An unscented Kalman filter (UKF), which employs a set of sigma points by deterministic sampling, avoids the error caused by linearization as in an extended Kalman filter (EKF). Based on the filter structural adaptation for describing various dynamic behaviours, the IMM nonlinear filtering provides an alternative for designing the adaptive filter in the ultra-tight GPS/INS integration. The use of IMM enables tuning of an appropriate value for the process of noise covariance so as to maintain good estimation accuracy and tracking capability. Two examples are provided to illustrate the effectiveness of the design and demonstrate the effective improvement in navigation estimation accuracy. A performance comparison among various filtering methods for ultra-tight integration of GPS and INS is also presented. The IMM based nonlinear filtering approach demonstrates the effectiveness of the algorithm for improved positioning performance.

A Novel Design for the Ultra-Tightly Coupled GPS/INS Navigation System

This paper presents a sensor fusion method for the Ultra-Tightly Coupled (UTC) Global Positioning System (GPS)/Inertial Navigation System (INS) integrated navigation. The UTC structure, also known as the deep integration, exhibits many advantages, e.g., disturbance and multipath rejection capability, improved tracking capability for dynamic scenarios and weak signals, and reduction of acquisition time. This architecture involves the integration of I (in-phase) and Q (quadrature) components from the correlator of a GPS receiver with the INS data. The Particle Filter (PF) exhibits superior performance as compared to an Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) in state estimation for the nonlinear, non-Gaussian system. To handle the problem of heavy-tailed probability distribution, one of the strategies is to incorporate the UKF into the PF as the proposal distribution, leading to the Unscented Particle Filter (UPF). The combination of an adaptive UPF and Fuzzy Logic Adaptive System (FLAS) is adopted for reducing the number of particles with sufficiently good results. The GPS tracking loops may lose lock due to the signals being weak, subjected to excessive dynamics or completely blocked. One of the principal advantages of the UTC structure is that a Doppler frequency derived from the INS is integrated with the tracking loops to improve the receiver tracking capability. The Doppler frequency shift is calculated and fed to the GPS tracking loops for elimination of the effect of stochastic errors caused by the Doppler frequency. In this paper, several nonlinear filtering approaches, including EKF, UKF, UPF and ‘FLAS assisted UPF’ (FUPF), are adopted for performance comparison for ultra-tight integration of GPS and INS. It is assumed that no outage occurs such that the inertial sensor errors can be properly corrected and accordingly the aiding information is working well. Two examples are provided for performance assessment for the various data fusion methods. The FUPF algorithm with Doppler velocity aiding demonstrates remarkable improvement, especially in the high dynamic environments, in navigation estimation accuracy with reduction of number of particles.

An innovative scheme for SINS/GPS ultra-tight integration system with low-grade IMU

In the traditional strapdown inertial navigation system/global positioning system (SINS/GPS) ultra-tight integration structure, the mutual aiding between SINS and GPS forms a positive feedback loop, through which measurement errors of both subsystems are coupled deeply. In signal jamming or/and dynamic conditions, the Doppler aiding error derived from the SINS using low-grade inertial measurement unit (IMU) can increase rapidly, and cause GPS measurement errors to be correlated with the SINS velocity errors. Such correlations can result in poor estimation accuracy of the integration Kalman filter, losing lock of tracking loops or even yielding system instability. To solve this problem, we propose to model tracking errors of the SINS aided phase lock loop and to derive a new tracking-error estimator. Then, an innovative scheme for SINS/GPS ultra-tight integration using low-grade IMU is investigated. Simulations experiments are implemented to verify this innovative scheme under challenging environments.

Theoretical analysis and application of Kalman filters for ultra-tight global position system/inertial navigation system integration

When a global position system (GPS) is combined with an inertial navigation system (INS) in the ultra-tight GPS/INS integrated navigation system, their performances are both optimized. However, different from loose and tight integration, in the ultra-tight integration, the non-linearity of Kalman measurements will seriously affect the filtering result. As the performance of the Kalman filter is radically affected by the modelling strategies, this paper will discuss it in depth. Firstly, the modelling of a traditional Kalman filter for ultra-tight integration is introduced by derivation and simulation experiments based on a single-frequency GPS software receiver. Then, the theoretical analysis of its performances on observability, controllability and stability is given. According to that, a novel extended Kalman filter for the ultra-tight integration is presented, using a Q (quadrature) signal from the GPS receiver correlator and a position and velocity from both the GPS and INS to form the measurements of the extended Kalman filter. New simulation experiments under the same initial conditions are carried out, and the comparison results show that the new method can provide better precision of all navigation parameters. However, it is noted that the curves of position and velocity errors have slight oscillation; the reason for this will be studied in the future.

Ultra-tightly Coupled GPS/Vehicle Sensor Integration for Land Vehicle Navigation

With the increasing demand for location dependent applications in land vehicles, modern vehicle systems are often equipped with Global Positioning System (GPS) receivers and vehicle sensors to provide position, velocity, and attitude information. This paper investigates an ultra-tight integration strategy to fuse GPS and a vehicle sensor configuration consisting of two horizontal accelerometers, a single vertical gyroscope, and wheel speed sensors. Data from a field test is analyzed in the tracking and navigation domains to verify the feasibility of implementing the proposed system. Results demonstrate that the ultra-tight approach is still beneficial under typical driving conditions even with a limited vehicle sensor configuration that cannot measure the full motion of the body.

Adaptive GPS Tracking Loop Bandwidth Tuning Using Fuzzy Control and Inertial Aiding for Missile Applications

Autonomous Navigation Systems (ANS) used in ballistic or cruise missiles are mostly dependent on very high grade Inertial Navigation System (INS). INS is a dead reckoning system and its navigation solution always drifts with time from the correct one. Using aiding from other navigation sensors such as Global Positioning System (GPS) can help getting much better navigation solution and can allow dependence on lower grade INS. Data fusion from both INS and GPS can be done through an Extended Kalman Filter (EKF) either by fusing navigation solution from both sensors in a loosely coupled (LC) technique, or by using Doppler measurements aiding to aid INS or both INS and GPS as in tightly coupled (TC) or tightly coupled with aiding (TCA) technique which is sometimes called Ultra-Tight (UT) integration. GPS usage has limitations in terms of missile high dynamics and signal interference. The GPS receiver requirements to avoid these problems are conflicting. The Phase Lock Loops (PLLs), used to track GPS signals, are required to have a bandwidth as narrow as possible to reduce the impact of signal interference. On the contrary, the loop bandwidth has to be as wide as possible to accommodate high signal dynamics. To solve this contradiction, a new adaptive GPS tracking loop bandwidth tuning algorithm is designed based on integrated INS/GPS through an EKF linked to a Fuzzy Logic Controller (FLC). This controller senses the vehicle dynamics and the jamming signal conditions and decides the bandwidth value according to those inputs. The Adaptive Fuzzy Ultra Tight (AFUT) GPS/INS integration architecture has been developed and assessed by simulation using SPIRENT GSS7700 GPS hardware simulator showing that it provides a significant anti-jam and dynamics margins over an INS/GPS with fixed