Improving the spaceborne GNSS-R altimetric precision based on the novel multilayer feedforward neural network weighted joint prediction model

Global navigation satellite system-reflection(GNSS-R)sea surface altimetry based on satellite constellation platforms has become a new research direction and inevitable trend,which can meet the altimetric precision at the global scale required for underwater navigation.At present,there are still research gaps for GNSS-R altimetry under this mode,and its altimetric capability cannot be specifically assessed.Therefore,GNSS-R satellite constellations that meet the global altimetry needs to be designed.Meanwhile,the matching precision prediction model needs to be established to quantitatively predict the GNSS-R constellation altimetric capability.Firstly,the GNSS-R constellations altimetric precision under different configuration parameters is calculated,and the mechanism of the influence of orbital altitude,orbital inclination,number of satellites and simulation period on the precision is analyzed,and a new multilayer feedforward neural network weighted joint prediction model is established.Secondly,the fit of the prediction model is verified and the performance capability of the model is tested by calculating the R2 value of the model as 0.9972 and the root mean square error(RMSE)as 0.0022,which indicates that the prediction capability of the model is excellent.Finally,using the novel multilayer feedforward neural network weighted joint prediction model,and considering the research results and realistic costs,it is proposed that when the constellation is set to an orbital altitude of 500 km,orbital inclination of 75and the number of satellites is 6,the altimetry precision can reach 0.0732 m within one year simulation period,which can meet the requirements of underwater navigation precision,and thus can provide a reference basis for subsequent research on spaceborne GNSS-R sea surface altimetry.

Surface texture formation in precision machining of direct laser deposited tungsten carbide

This paper focuses on an analysis of the surface texture formed during precision machining of tungsten carbide. The work material was fabricated using direct laser deposition （DLD） technology. The experiment included precision milling of tungsten carbide samples with a monolithic torus cubic boron nitride tool and grinding with diamond and alumina cup wheels. An optical surface profiler was applied to the measurements of surface textures and roughness profiles. In addition, the micro-geometry of the milling cutter was measured with the appli- cation of an optical device. The surface roughness height was also estimated with the application of a model, which included kinematic-geometric parameters and minimum uncut chip thickness. The research revealed the occurrence of micro-grooves on the machined surface. The surface roughness height calculated on the basis of the traditional kinematic-geometric model was incompatible with the measurements. However, better agreement between the theoretical and experimental values was observed for the minimum uncut chip thickness model.

Novel Design Method of COG Measurement System Via Supporting Reaction Method

Center of gravity(COG)is an important parameter of projectiles and rockets,for which supporting reaction method(or support reaction method)is an important COG measurement method.Based on this supporting reaction method a novel design method is proposed to determine the key design parameters of the COG measurement system.The method can quantitatively analyze the influence of the design parameters on the COG accuracy,in the measurement system designed with supporting reaction method.Using the principle of static balance,the error propagation theory,and the system accuracy analysis method,the equal-range required sensor precision(RSP)surface and non-equal-range required sensor pair precision(RSPP)adapted surface are adopted.The influence of random errors(like sensor accuracy and distance calibration accuracy)is analyzed.The selection strategy of equal-range and non-equal-range sensors is chosen,and then the recommended calibration accuracy values are obtained.For the quality detection accuracy of±0.6 kg and the axial COG detection accuracy of±1.5 mm,the RSP surface is drawn by the proposed method,and the force sensor with±0.23 kg detection accuracy is selected.The experimental verification meets the accuracy requirements and verifies the effectiveness of the proposed design method for the system parameters of the COG measurement equipment.