Fast acquisition of L2C CL codes based on combination of hyper codes and averaging correlation

This paper provides a direct and fast acquisition algorithm of civilian long length（CL） codes in the L2 civil（L2C） signal. The proposed algorithm simultaneously reduces the number of fast Fourier transformation（FFT） correlation through hyper code technique and the amount of points in every FFT correlation by using an averaging correlation method. To validate the proposed acquisition performance, the paper applies this algorithm to the real L2C signal collected by the global positioning system（GPS） L2C intermediate frequency（IF） signal sampler—SIS100L2C. The acquisition results show that the proposed modified algorithm can acquire the code phase accurately with less calculation and its acquisition performance is better than the single hyper code method.

Identification of multiple inputs single output errors-in-variables system using cumulant

A higher-order cumulant-based weighted least square（HOCWLS） and a higher-order cumulant-based iterative least square（HOCILS） are derived for multiple inputs single output（MISO） errors-in-variables（EIV） systems from noisy input/output data. Whether the noises of the input/output of the system are white or colored, the proposed algorithms can be insensitive to these noises and yield unbiased estimates. To realize adaptive parameter estimates, a higher-order cumulant-based recursive least square（HOCRLS） method is also studied. Convergence analysis of the HOCRLS is conducted by using the stochastic process theory and the stochastic martingale theory. It indicates that the parameter estimation error of HOCRLS consistently converges to zero under a generalized persistent excitation condition. The usefulness of the proposed algorithms is assessed through numerical simulations.

Resonance Characteristics of Piezoelectric Resonator Based on Digital Driving Circuit of Field-Programmable Gate Array

Piezoelectric resonators are widely used in frequency reference devices, mass sensors, resonant sensors(such as gyros and accelerometers), etc. Piezoelectric resonators usually work in a special resonant mode. Obtaining working resonant mode with high quality is key to improve the performance of piezoelectric resonators. In this paper, the resonance characteristics of a rectangular lead zirconium titanate(PZT) piezoelectric resonator are studied. On the basis of the field-programmable gate array(FPGA) embedded system, direct digital synthesizer(DDS) and automatic gain controller(AGC) are used to generate the driving signals with precisely adjustable frequency and amplitude. The driving signals are used to excite the piezoelectric resonator to the working vibration mode. The influence of the connection of driving electrodes and voltage amplitude on the vibration of the resonator is studied. The quality factor and vibration linearity of the resonator are studied with various driving methods mentioned in this paper. The resonator reaches resonant mode at 330 kHz by different driving methods.The relationship between resonant amplitude and driving signal amplitude is linear. The quality factor reaches over 150 by different driving methods. The results provide a theoretical reference for the efficient excitation of the piezoelectric resonator.

M2C-GVIO:motion manifold constraint aided GNSS-visual-inertial odometry for ground vehicles

Visual-Inertial Odometry(VIO)has been developed from Simultaneous Localization and Mapping(SLAM)as a lowcost and versatile sensor fusion approach and attracted increasing attention in ground vehicle positioning.However,VIOs usually have the degraded performance in challenging environments and degenerated motion scenarios.In this paper,we propose a ground vehicle-based VIO algorithm based on the Multi-State Constraint Kalman Filter(MSCKF)framework.Based on a unifed motion manifold assumption,we derive the measurement model of manifold constraints,including velocity,rotation,and translation constraints.Then we present a robust flter-based algorithm dedicated to ground vehicles,whose key is the real-time manifold noise estimation and adaptive measurement update.Besides,GNSS position measurements are loosely coupled into our approach,where the transformation between GNSS and VIO frame is optimized online.Finally,we theoretically analyze the system observability matrix and observability measures.Our algorithm is tested on both the simulation test and public datasets including Brno Urban dataset and Kaist Urban dataset.We compare the performance of our algorithm with classical VIO algorithms(MSCKF,VINS-Mono,R-VIO,ORB_SLAM3)and GVIO algorithms(GNSS-MSCKF,VINS-Fusion).The results demonstrate that our algorithm is more robust than other compared algorithms,showing a competitive position accuracy and computational efciency.

H_∞ Inverse Optimal Adaptive Fault-Tolerant Attitude Control for Flexible Spacecraft with Input Saturation

An adaptive inverse optimal attitude controller for flexible spacecraft with fault-free actuator is designed based on adaptive control Lyapunov function and inverse optimal methodology subjected to unknown parameter uncertainties,external disturbances and input saturation.The partial loss of actuator effectiveness and the additive faults are considered simultaneously to deal with actuator faults,and the prior knowledge of bounds on the effectiveness factors of the actuators is assumed to be unknown.A fault-tolerant control version is designed to handle the system with actuator fault by introducing a parameter update law to estimate the lower bound of the partial loss of actuator effectiveness faults.The proposed fault-tolerant attitude controller ensures robustness and stabilization,and it achieves H_∞ optimality with respect to a family of cost functionals.The usefulness of the proposed algorithms is assessed and compared with the conventional approaches through numerical simulations.