DM Code Key Point Detection Algorithm Based on CenterNet

Data Matrix(DM)codes have been widely used in industrial production.The reading of DM code usually includes positioning and decoding.Accurate positioning is a prerequisite for successful decoding.Traditional image processing methods have poor adaptability to pollution and complex backgrounds.Although deep learning-based methods can automatically extract features,the bounding boxes cannot entirely fit the contour of the code.Further image processing methods are required for precise positioning,which will reduce efficiency.Because of the above problems,a CenterNet-based DM code key point detection network is proposed,which can directly obtain the four key points of the DM code.Compared with the existing methods,the degree of fitness is higher,which is conducive to direct decoding.To further improve the positioning accuracy,an enhanced loss function is designed,including DM code key point heatmap loss,standard DM code projection loss,and polygon Intersection-over-Union(IoU)loss,which is beneficial for the network to learn the spatial geometric characteristics of DM code.The experiment is carried out on the self-made DM code key point detection dataset,including pollution,complex background,small objects,etc.,which uses the Average Precision(AP)of the common object detection metric as the evaluation metric.AP reaches 95.80%,and Frames Per Second(FPS)gets 88.12 on the test set of the proposed dataset,which can achieve real-time performance in practical applications.

AUTOMATED IMAGE MATCHING WITH CODED POINTS IN STEREOVISION MEASUREMENT

A coding-based method to solve the image matching problems in stereovision measurement is presented. The solution is to add and append an identity ID to the retro-reflect point, so it can be identified efficiently under the complicated circumstances and has the characteristics of rotation, zooming, and deformation independence. Its design architecture and implementation process in details based on the theory of stereovision measurement are described. The method is effective on reducing processing data time, improving accuracy of image matching and automation of measuring system through experiments.

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.