Nonlinear Complementary Filter for Attitude Estimation by Fusing Inertial Sensors and a Camera.

Using a standalone camera for pose estimation has been quite a standard task. However, the point correspondence-based algorithms require at least four feature points in the field of view. This paper considers the situation that there are only two feature points. Focusing on the attitude estimation, we propose to fuse a camera with low-cost inertial sensors based on a nonlinear complementary filter design. An implicit geometry measurement model is derived using two feature points in an image. This geometry measurement is fused with the angle rate measurement and vector measurement from inertial sensors using the proposed nonlinear complementary filter with only two parameters to be adjusted. The proposed nonlinear complementary filter is posed directly on the special orthogonal group SO(3). Based on the theory of nonlinear system stability analysis, the proposed filter ensures locally asymptotic stability. A quaternion-based discrete implementation of the filter is also given in this paper for computational efficiency. The proposed algorithm is validated using a smartphone with built-in inertial sensors and a rear camera. The experimental results indicate that the proposed algorithm outperforms all the compared counterparts in estimated accuracy and provides competitive computational complexity.

Fault Detection and Exclusion for Tightly Coupled GNSS/INS System Considering Fault in State Prediction.

To ensure navigation integrity for safety-critical applications, this paper proposes an efficient Fault Detection and Exclusion (FDE) scheme for tightly coupled navigation system of Global Navigation Satellite Systems (GNSS) and Inertial Navigation System (INS). Special emphasis is placed on the potential faults in the Kalman Filter state prediction step (defined as "filter fault"), which could be caused by the undetected faults occurring previously or the Inertial Measurement Unit (IMU) failures. The integration model is derived first to capture the features and impacts of GNSS faults and filter fault. To accommodate various fault conditions, two independent detectors, which are respectively designated for GNSS fault and filter fault, are rigorously established based on hypothesis-test methods. Following a detection event, the newly-designed exclusion function enables (a) identifying and removing the faulty measurements and (b) eliminating the effect of filter fault through filter recovery. Moreover, we also attempt to avoid wrong exclusion events by analyzing the underlying causes and optimizing the decision strategy for GNSS fault exclusion accordingly. The FDE scheme is validated through multiple simulations, where high efficiency and effectiveness have been achieved in various fault scenarios.

A Subset-Reduced Method for FDE ARAIM of Tightly-Coupled GNSS/INS.

The advanced receiver autonomous integrity monitoring (advanced RAIM, ARAIM) is the next generation of RAIM which is widely used in civil aviation. However, the current ARAIM needs to evaluate hundreds of subsets, which results in huge computational loads. In this paper, a method using the subset excluding entire constellation to evaluate the single satellite fault subsets and the simultaneous multiple satellites fault subsets is presented. The proposed ARAIM algorithm is based on the tight integration of the global navigation satellite system (GNSS) and inertial navigation system (INS). The number of subsets that the proposed GNSS/INS ARAIM needs to consider is about 2% of that of the current ARAIM, which reduces the computational load dramatically. The detailed fault detection (FD) process and fault exclusion (FE) process of the proposed GNSS/INS ARAIM are provided. Meanwhile, the method to obtain the FD-only integrity bound and the after-exclusion integrity bound is also presented in this paper. The simulation results show that the proposed GNSS/INS ARAIM is able to find the failing satellite accurately and its integrity performance is able to meet the integrity requirements of CAT-I precision approach.

Multisensor Parallel Largest Ellipsoid Distributed Data Fusion with Unknown Cross-Covariances.

As the largest ellipsoid (LE) data fusion algorithm can only be applied to two-sensor system, in this contribution, parallel fusion structure is proposed to introduce the LE algorithm into a multisensor system with unknown cross-covariances, and three parallel fusion structures based on different estimate pairing methods are presented and analyzed. In order to assess the influence of fusion structure on fusion performance, two fusion performance assessment parameters are defined as Fusion Distance and Fusion Index. Moreover, the formula for calculating the upper bounds of actual fused error covariances of the presented multisensor LE fusers is also provided. Demonstrated with simulation examples, the Fusion Index indicates fuser's actual fused accuracy and its sensitivity to the sensor orders, as well as its robustness to the accuracy of newly added sensors. Compared to the LE fuser with sequential structure, the LE fusers with proposed parallel structures not only significantly improve their properties in these aspects, but also embrace better performances in consistency and computation efficiency. The presented multisensor LE fusers generally have better accuracies than that of covariance intersection (CI) fusion algorithm and are consistent when the local estimates are weakly correlated.

An Analytical Model for BDS B1 Spreading Code Self-Interference Evaluation Considering NH Code Effects.

The short spreading code used by the BeiDou Navigation Satellite System (BDS) B1-I or GPS Coarse/Acquistiion (C/A) can cause aggregately undesirable cross-correlation between signals within each single constellation. This GPS-to-GPS or BDS-to-BDS correlation is referred to as self-interference. A GPS C/A code self-interference model is extended to propose a self-interference model for BDS B1, taking into account the unique feature of the B1-I signal transmitted by BDS medium Earth orbit (MEO) and inclined geosynchronous orbit (IGSO) satellites-an extra Neumann-Hoffmann (NH) code. Currently there is no analytical model for BDS self-interference and a simple three parameter analytical model is proposed. The model is developed by calculating the spectral separation coefficient (SSC), converting SSC to equivalent white noise power level, and then using this to calculate effective carrier-to-noise density ratio. Cyclostationarity embedded in the signal offers the proposed model additional accuracy in predicting B1-I self-interference. Hardware simulator data are used to validate the model. Software simulator data are used to show the impact of self-interference on a typical BDS receiver including the finding that self-interference effect is most significant when the differential Doppler between desired and undesired signal is zero. Simulation results show the aggregate noise caused by just two undesirable spreading codes on a single desirable signal could lift the receiver noise floor by 3.83 dB under extreme C/N0 (carrier to noise density ratio) conditions (around 20 dB-Hz). This aggregate noise has the potential to increase code tracking standard deviation by 11.65 m under low C/N0 (15-19 dB-Hz) conditions and should therefore, be avoided for high-sensitivity applications. Although the findings refer to Beidou system, the principle weakness of the short codes illuminated here are valid for other satellite navigation systems.

GNSS Spoofing Network Monitoring Based on Differential Pseudorange.

Spoofing is becoming a serious threat to various Global Navigation Satellite System (GNSS) applications, especially for those that require high reliability and security such as power grid synchronization and applications related to first responders and aviation safety. Most current works on anti-spoofing focus on spoofing detection from the individual receiver side, which identifies spoofing when it is under an attack. This paper proposes a novel spoofing network monitoring (SNM) mechanism aiming to reveal the presence of spoofing within an area. Consisting of several receivers and one central processing component, it keeps detecting spoofing even when the network is not attacked. The mechanism is based on the different time difference of arrival (TDOA) properties between spoofing and authentic signals. Normally, TDOAs of spoofing signals from a common spoofer are identical while those of authentic signals from diverse directions are dispersed. The TDOA is measured as the differential pseudorange to carrier frequency ratio (DPF). In a spoofing case, the DPFs include those of both authentic and spoofing signals, among which the DPFs of authentic are dispersed while those of spoofing are almost overlapped. An algorithm is proposed to search for the DPFs that are within a pre-defined small range, and an alarm will be raised if several DPFs are found within such range. The proposed SNM methodology is validated by simulations and a partial field trial. Results show 99.99% detection and 0.01% false alarm probabilities are achieved. The SNM has the potential to be adopted in various applications such as (1) alerting dedicated users when spoofing is occurring, which could significantly shorten the receiver side spoofing cost; (2) in combination with GNSS performance monitoring systems, such as the Continuous Operating Reference System (CORS) and GNSS Availability, Accuracy, Reliability anD Integrity Assessment for Timing and Navigation (GAARDIAN) System, to provide more reliable monitoring services.

Weak and Dynamic GNSS Signal Tracking Strategies for Flight Missions in the Space Service Volume.

Weak-signal and high-dynamics are of two primary concerns of space navigation using GNSS (Global Navigation Satellite System) in the space service volume (SSV). The paper firstly defines a reference assumption third-order phase-locked loop (PLL) as the baseline of an onboard GNSS receiver, and proves the incompetence of this conventional architecture. Then an adaptive four-state Kalman filter (KF)-based algorithm is introduced to realize the optimization of loop noise bandwidth, which can adaptively regulate its filter gain according to the received signal power and line-of-sight (LOS) dynamics. To overcome the matter of losing lock in weak-signal and high-dynamic environments, an open loop tracking strategy aided by an inertial navigation system (INS) is recommended, and the traditional maximum likelihood estimation (MLE) method is modified in a non-coherent way by reconstructing the likelihood cost function. Furthermore, a typical mission with combined orbital maneuvering and non-maneuvering arcs is taken as a destination object to test the two proposed strategies. Finally, the experiment based on computer simulation identifies the effectiveness of an adaptive four-state KF-based strategy under non-maneuvering conditions and the virtue of INS-assisted methods under maneuvering conditions.