Design and Parameter Optimization of Zero Position Code Considering Diffraction Based on Deep Learning Generative Adversarial Networks

Absolute measurement has consistently been the primary focus in the development of precision linear and angular displace-ment measurements.The scheme design of binary zero position codes is an important factor for absolute measurement.Designing and optimizing high-bit zero position codes with over 100 bits face considerable challenges.Simultaneously,the working parameters of zero position codes[unit code width(b),distance(d),and yaw angle(α)]remarkably affect their post-installation performance,particularly in absolute positioning and limit code application in multi-degree-of-freedom measurement schemes.This study addresses these challenges by proposing a design method for zero position codes that considers diffraction based on generative adversarial networks and aims to explore a design with increased efficiency and accuracy as well as optimization for high-bit zero position codes.Additionally,the tolerance range of zero positioning per-formance for each working parameter is examined.By leveraging the adversarial network structure,this study generates the optimization of a 150-bit code and processes the tests of the zero position code by using simulation results.The following working parameter ranges for code design are recommended on the basis of theoretical and experimental results:b greater than 10μm,d andαwithin 1000μm and 3490μrad,and avoidance of intervals with sharp changes in the full width at half maximum.The proposed code design and parameter optimization lay a solid foundation for research and engineering appli-cations in absolute measurement field and have considerable potential for generalization and wide applicability.

Carrier phase-based ionospheric observables using PPP models

The ionosphere is one of the major error sources in Global Navigation Satellite System （GNSS） posi- tioning, navigation and timing. Estimating the ionospheric delays precisely is of great interest in the GNSS community. To date, GNSS observables for ionospheric estimation are most commonly based on carrier phase smoothed code measurements. However, leveling errors, which affect the performance of ionospheric modeling and differential code bias （DCB） estimation, exist in the carrier phase smoothed code observations. Such leveling errors are caused by the multipath and the short-term variation of DCB. To reduce these leveling errors, this paper investigates and estimates the ionospheric delays based on carrier phase measurements without the leveling errors. The line-of-sight ionospheric observables with high precision are calculated using precise point positioning （PPP） techniques, in which carrier phase measurements are the principal observables. Ionosphere-free and UofC PPP models are applied and compared for their effectiveness to minimize the leveling errors. To assess the leveling errors, single difference of ionospheric observables for a short baseline is examined. Results show that carrier phase- derived ionospheric observables from PPP techniques can effectively reduce the leveling errors. Furthermore, we compared the PPP ionosphere estimation model with the conventional carrier phase smoothed code method to assess the bias consistency and investigate the biases in the ionospheric observables.

Preliminary assessment of the navigation and positioning performance of BeiDou regional navigation satellite system

BeiDou regional navigation satellite system （BDS） also called BeiDou-2 has been in full operation since December 27, 2012. It consists of 14 satellites, including 5 satellites in Geostationary Orbit （GEO）, 5 satellites in Inclined Geosynchronous Orbit （IGSO）, and 4 satellites in Medium Earth Orbit （MEO）. In this paper, its basic navigation and positioning performance are evaluated preliminarily by the real data collected in Beijing, including satellite visibility, Position Dilution of Precision （PDOP） value, the precision of code and carrier phase measurements, the accuracy of single point positioning and differential position- ing and ambiguity resolution （AR） performance, which are also compared with those of GPS. It is shown that the precision of BDS code and carrier phase measurements are about 33 cm and 2 mm, respectively, which are comparable to those of GPS, and the accuracy of BDS single point positioning has satisfied the design requirement. The real-time kinematic positioning is also feasible by BDS alolae in the opening condition, since its fixed rate and reliability of single-epoch dual-frequency AR is comparable to those of GPS. The accuracy of BDS carrier phase differential positioning is better than 1 cm for a very short baseline of 4.2 m and 3 cm for a short baseline of 8.2 km, which is on the same level with that of GPS. For the combined BDS and GPS, the fixed rate and reliability of single-epoch AR and the positioning accuracy are improved significantly. The accu- racy of BDS/GPS carrier phase differential positioning is about 35 and 20 % better than that of GPS for two short baseline tests in this study. The accuracy of BDS code differential positioning is better than 2.5 m. However it is worse than that of GPS, which may result from large code multipath errors of BDS GEO satellite measurements.

Vision algorithms for fixed-wing unmanned aerial vehicle landing system

Autonomous landing has become a core technology of unmanned aerial vehicle（UAV）guidance,navigation and control system

Model-Based Embedded Compiled Software Fault Positioning

Software fault positioning is one of the most effective activities in program debugging. In this paper, we propose a model-based fault positioning method to detect the faults of embedded program without source code. The system takes the machine code of embedded software as input and translates the code into high-level language C with the software reverse engineering program. Then, the static analysis on the high-level program is taken to obtain a control flow graph（CFG）, which is denoted as a node-tree and each node is a basic block. According to the faults found by the field testing, we construct a fault model by extracting the features of the faulty code obtained by ranking the Ochiai coefficient of basic blocks. The model can be effectively used to locate the faults of the embedded program. Our method is evaluated on ST chips of the smart meter with the corresponding source code. The experiment shows that the proposed method has an effectiveness about 87% on the fault detection.