In this paper, we propose a robust adaptive cubature Kalman filter (CKF) to deal with the problem of an inaccurately known system model and noise statistics. In order to overcome the kinematic model error, we introduce an adaptive factor to adjust the covariance matrix of state prediction, and process the influence introduced by dynamic disturbance error. Aiming at overcoming the abnormality error, we propose the robust estimation theory to adjust the CKF algorithm online. The proposed adaptive CKF can detect the degree of gross error and subsequently process it, so the influence produced by the abnormality error can be solved. The paper also studies a typical application system for the proposed method, which is the ultra-tightly coupled navigation system of a hypersonic vehicle. Highly dynamical scene experimental results show that the proposed method can effectively process errors aroused by the abnormality data and inaccurate model, and has better tracking performance than UKF and CKF tracking methods. Simultaneously, the proposed method is superior to the tracing method based on a single-modulating loop in the tracking performance. Thus, the stable and high-precision tracking for GPS satellite signals are preferably achieved and the applicability of the system is promoted under the circumstance of high dynamics and weak signals. The effectiveness of the proposed method is verified by a highly dynamical scene experiment.

Alkali vapor cells are the core components of atomic sensing instruments such as atomic gyroscopes, atomic magnetometers, atomic clocks, etc. Emerging integrated atomic sensing devices require high-performance miniaturized alkali vapor cells, especially micro-fabricated vapor cells. In this review, bonding methods for vapor cells of this kind are summarized in detail, including anodic bonding, sacrificial micro-channel bonding, and metal thermocompression bonding. Compared with traditional through-lighting schemes, researchers have developed novel methods for micro-fabricated vapor cells under both single- and double-beam schemes. In addition, emerging packaging methods for alkali metals in micro-fabricated vapor cells can be categorized as physical or chemical approaches. Physical methods include liquid transfer and wax pack filling. Chemical methods include the reaction of barium azide with rubidium chloride, ultraviolet light decomposition (of rubidium azide), and the high-temperature electrolysis of rubidium-rich glass. Finally, the application trend of micro-fabricated alkali vapor cells in the field of micro-scale gyroscopes, micro-scale atomic clocks, and especially micro-scale biomagnetometers is reviewed. Currently, the sensing industry has become a major driving force for the miniaturization of atomic sensing devices, and in the near future, the micro-fabricated alkali vapor cell technology of atomic sensing devices may experience extensive developments.

Magnetoencephalography (MEG), leveraging magnetic signal detection, is a clinically validated neuroimaging technique known for its high spatiotemporal resolution and non-invasive nature, effectively mitigating damage to brain function and mortality rates in preoperative epilepsy evaluations. Optically pumped magnetometer (OPM), a quantum sensor, emerges as the new generation of MEG detection device benefiting from its low cost, wearable, motion robustness, and lifespan-compliant. While in the context of medical applications, the OPM-MEG system requires overcoming several barriers. Magnetic field interference has the propensity to impact the OPM, triggering output errors and thus diminish the quality of neuromagnetic imaging. In this review, we thoroughly explore the advantages and limitations of hardware-based magnetic field interference suppression techniques, and envision the implementable suppression strategies focusing on the pressing demand for the mobile MEG. The anticipated iterative enhancements in magnetic field interference suppression technology hold the promise of driving the application of OPM-MEG in more naturalistic, multi-person interactive paradigms in cognitive neuroscience, thus facilitating the development of novel therapeutic approaches for neurological and psychiatric disorders.

Distributed Position and Orientation System (POS) uses transfer alignment to accurately measure multi-node time-spatial reference information, which is urgently demanded to compensate motion error of imaging sensors for aerial survey. The lever-arm deformation in transfer alignment will result in nonlinear error and time-varying measurement noise covariance, which decreases the accuracy of real-time estimation. In order to solve this problem, a nonlinear transfer alignment method of distributed POS based on Adaptive Second-order Divided Difference Filter (ADDF2) is proposed. First, transfer alignment model for distributed POS is established. Furthermore, an ADDF2 based on adaptive innovation estimation is proposed to solve the nonlinear problem and adaptively adjust the measurement noise covariance matrix of transfer alignment in real-time. The flight experiment results show that the proposed method is effective to improve the precision of distributed POS.

With the development of the novel remote sensing system such as array antenna interference synthetic aperture radar (InSAR), it is in urgent demand to design and develop an airborne distributed position and orientation system (D- POS) to provide multi-node time-spatial reference information accurately. To solve the problem, this paper describes a novel design and fabrication of DPOS, which integrates the main strapdown inertial navigation system (SINS), global position satellite (GPS), multiple slave inertial measurement units (IMUs) and distributed navigation processing computer system (DNPCS). In the proposed system, multiple digital signal processors(multi- DSPs) are used for multiple inertial navigation solutions and Kalman filter(KF) computations, and a field programmable gate array (FPGA) is used for creating an efficient interface of the GPS and multiple IMUs with the multi-DSPs. This also helps reduce the count of the total chips, resulting in a compact system. The system is designed to provide synchronous multi-node real-time high-precision navigation solutions with an update of 200Hz. In order to verify the performance of DPOS, the real flight test, which combined InSAR and DPOS, was conducted and showed the proposed system can help compensate the motion error of the high-resolution interference mapping more efficiently than the single POS.