Interpretable STAP Algorithm Based on Deep Convolutional Neural Network

In practical settings, the efficacy of Space-Time Adaptive Processing (STAP) algorithms relies on acquiring sufficient Independent Identically Distributed (IID) samples. However, sparse recovery STAP method encounters challenges like model parameter dependence and high computational complexity. Furthermore, current deep learning STAP methods lack interpretability, posing significant hurdles in debugging and practical applications for the network. In response to these challenges, this paper introduces an innovative method: a Multi-module Deep Convolutional Neural Network (MDCNN). This network blends data- and model-driven techniques to precisely estimate clutter covariance matrices, particularly in scenarios where training samples are limited. MDCNN is built based on four key modules: mapping, data, priori and hyperparameter modules. The front- and back-end mapping modules manage the pre- and post-processing of data, respectively. During each equivalent iteration, a group of data and priori modules collaborate. The core network is formed by multiple groups of these two modules, enabling multiple equivalent iterative optimizations. Further, the hyperparameter module adjusts the trainable parameters in equivalent iterations. These modules are developed with precise mathematical expressions and practical interpretations, remarkably improving the network’s interpretability. Performance evaluation using real data demonstrates that our proposed method slightly outperforms existing small-sample STAP methods in nonhomogeneous clutter environments while significantly reducing computational time

Improved Model for Beam-Wave Interaction with Ohmic Losses and Reflections of Sheet Beam Traveling Wave Tubes

In this article, an improved model for the beam-wave interaction of sheet beam in traveling wave tubes (TWTs) considering ohmic losses and reflections is presented. The ohmic losses are obtained by field analysis and equivalent method. The space charge magnetic field is derived from the active Helmholtz's equation. An algorithm to obtain the S-matrix by the equivalent circuit method is presented. The relativistic Boris method is applied to accelerate macroparticles. The exchanged power is computed by the work the electromagnetic field applied to the macroparticles. The theoretical model is applied for validation to a G-band staggered double vane TWT and validated in comparison with CST Particle Studio and simulations without losses and reflections. The convergence of this algorithm is also discussed. The simulation time of the model is substantial faster than 3-D particle-in-cell (PIC) simulations

Payload Identification and Gravity/Inertial Compensation for Six-Dimensional Force/Torque Sensor with a Fast and Robust Trajectory Design Approach

In the robot contact operation, the robot relies on the multi-dimensional force/torque sensor installed at the end to sense the external contact force. When the effective load and speed of the robot are large, the gravity/inertial force generated by it will have a non-negligible impact on the output of the force sensor, which will seriously affect the accuracy and effect of the force control. The existing identification algorithm time is often longer, which also affects the efficiency of force control operations. In this paper, a self-developed multi-dimensional force sensor with integrated gravity/inertial force sensing function is used to directly measure the resultant force. Further, a method for the rapid identification of payload based on excitation trajectory is proposed. Firstly, both a gravity compensation algorithm and an inertial force compensation algorithm are introduced. Secondly, the optimal spatial recognition pose based on the excitation trajectory was designed, and the excitation trajectory of each joint is represented by a finite Fourier series. The least square method is used to calculate the identification parameters of the load, the gravity, and inertial force. Finally, the experiment was verified on the robot. The experimental results show that the algorithm can quickly identify the payload, and it is faster and more accurate than other algorithms

Spatial and Temporal Evolution Analysis of Industrial Green Technology Innovation Efficiency in the Yangtze River Economic Belt

As a fusion point of innovation-driven green development, green technology innovation has become an essential engine for green transformation and high-quality economic development of the Yangtze River Economic Belt. Based on the panel data of 110 cities in the Yangtze River Economic Belt from 2006 to 2020, this paper uses the super-SBM model to measure the efficiency of industrial green technology innovation. Then, the Dagum Gini coefficient and its subgroup decomposition method, kernel density estimation, and the spatial Markov chain will discuss the convergence characteristics and dynamic evolution law of industrial green technology innovation efficiency in the Yangtze River Economic Belt. The results indicate several key points. (1) On the whole, the industrial green innovation efficiency of the Yangtze River Economic Belt shows a trend of the “N” type, which increases slowly at first and then decreases and then increases, and shows a non-equilibrium feature of “east high and west low” in space. (2) The average GML index of industrial green technology innovation efficiency in the Yangtze River Economic Belt is greater than 1, and technological progress is the main driving force in promoting efficiency growth. (3) There are spatial and temporal differences in industrial green technological innovation efficiency in the Yangtze River Economic Belt. Interregional differences and hypervariable density are the primary sources of overall differences. (4) During the study period, the absolute difference in industrial green technology innovation efficiency among regions showed a trend of “expansion-reduction-expansion”, and the innovation efficiency gradually converged to a single equilibrium point. (5) The industrial green technology innovation efficiency transfer in the Yangtze River Economic Belt shows a specific spatial dependence. Accordingly, policy suggestions are put forward to further improve industrial green technological innovation in the Yangtze River Economic Belt

Path Planning Based on NURBS for Hyper-Redundant Manipulator Used in Narrow Space

Hyper-redundant manipulators with multiple degrees of freedom have special application prospects in narrow spaces, such as detection in small spaces in aerospace, rescue on-site disaster relief, etc. In order to solve the problems of complex obstacle avoidance planning and inverse solution selection of a hyper-redundant robot in a narrow space, a cubic B-spline curve based on collision-free trajectory using environmental edge information is planned. Firstly, a hyper-redundant robot composed of four pairs of double UCR (Universal-Cylindrical-Revolute) parallel mechanisms (2R1T, 2 Rotational DOFs and 1 Translation DOF) in series to realize flexible obstacle avoidance motion in narrow space is designed. The trajectory point envelope of a single UCR and the workspace of a single pair of UCR in Cartesian space based on the motion constraint boundaries of each joint are obtained. Then, the constraint control points according to the edge information of the obstacle are obtained, and the obstacle avoidance trajectory in the constrained space is planned by combining the A* algorithm and cubic B-spline algorithm. Finally, a variety of test scenarios are built to verify the obstacle avoidance planning algorithm. The results show that the proposed algorithm reduces the computational complexity of the obstacle avoidance process and enables the robot to complete flexible obstacle avoidance movement in the complex narrow space

Path Planning Based on NURBS for Hyper-Redundant Manipulator Used in Narrow Space

Hyper-redundant manipulators with multiple degrees of freedom have special application prospects in narrow spaces, such as detection in small spaces in aerospace, rescue on-site disaster relief, etc. In order to solve the problems of complex obstacle avoidance planning and inverse solution selection of a hyper-redundant robot in a narrow space, a cubic B-spline curve based on collision-free trajectory using environmental edge information is planned. Firstly, a hyper-redundant robot composed of four pairs of double UCR (Universal-Cylindrical-Revolute) parallel mechanisms (2R1T, 2 Rotational DOFs and 1 Translation DOF) in series to realize flexible obstacle avoidance motion in narrow space is designed. The trajectory point envelope of a single UCR and the workspace of a single pair of UCR in Cartesian space based on the motion constraint boundaries of each joint are obtained. Then, the constraint control points according to the edge information of the obstacle are obtained, and the obstacle avoidance trajectory in the constrained space is planned by combining the A* algorithm and cubic B-spline algorithm. Finally, a variety of test scenarios are built to verify the obstacle avoidance planning algorithm. The results show that the proposed algorithm reduces the computational complexity of the obstacle avoidance process and enables the robot to complete flexible obstacle avoidance movement in the complex narrow space

Experimental Study of Robotic Polishing Process for Complex Violin Surface

This paper presents a robotic polishing process for complex violin surfaces to increase efficiency and minimize the cost and consumed time caused by using labor and traditional polishing machines. The polishing process is implemented based on modeling a smooth path, controlled contact force embedded with gravity compensation and material removal depth. A cubic Non-Uniform Rational Bases-Spline (NURBS) interpolation curve combined with an S-curve trajectory model is used to generate a smooth polishing path on a complex violin surface to achieve stable motion during the polishing process. An online admittance controller added to the fast gravity compensation algorithm maintains an accurate polishing force for equal removal depth on all polished surface areas. Then, based on Pythagorean theory, the removal depth model is calculated for the violin’s complex surface before and after polishing to estimate the accuracy of the polishing process. Experimental studies were conducted by polishing a wooden surface using the 6DOF robot manipulator to validate this methodology. The experimental results demonstrated that the robot had accurate polishing force based on the online admittance controller with gravity compensation. It also showed a precise proportional uniformity of removal depths at the different normal forces of 10, 15, and 20 N. The final results indicated that the proposed experimental polishing approach is accurate and polishes complex surfaces effectively

Multi-Robot Trajectory Planning and Position/Force Coordination Control in Complex Welding Tasks

In this paper, the trajectory planning and position/force coordination control of multi-robot systems during the welding process are discussed. Trajectory planning is the basis of the position/ force cooperative control, an object-oriented hierarchical planning control strategy is adopted firstly, which has the ability to solve the problem of complex coordinate transformation, welding process requirement and constraints, etc. Furthermore, a new symmetrical internal and external adaptive variable impedance control is proposed for position/force tracking of multi-robot cooperative manipulators. Based on this control approach, the multi-robot cooperative manipulator is able to track a dynamic desired force and compensate for the unknown trajectory deviations, which result from external disturbances and calibration errors. In the end, the developed control scheme is experimentally tested on a multi-robot setup which is composed of three ESTUN industrial manipulators by welding a pipe-contact-pipe object. The simulations and experimental results are strongly proved that the proposed approach can finish the welding task smoothly and achieve a good position/force tracking performance

Experimental Study of Robotic Polishing Process for Complex Violin Surface

This paper presents a robotic polishing process for complex violin surfaces to increase efficiency and minimize the cost and consumed time caused by using labor and traditional polishing machines. The polishing process is implemented based on modeling a smooth path, controlled contact force embedded with gravity compensation and material removal depth. A cubic Non-Uniform Rational Bases-Spline (NURBS) interpolation curve combined with an S-curve trajectory model is used to generate a smooth polishing path on a complex violin surface to achieve stable motion during the polishing process. An online admittance controller added to the fast gravity compensation algorithm maintains an accurate polishing force for equal removal depth on all polished surface areas. Then, based on Pythagorean theory, the removal depth model is calculated for the violin’s complex surface before and after polishing to estimate the accuracy of the polishing process. Experimental studies were conducted by polishing a wooden surface using the 6DOF robot manipulator to validate this methodology. The experimental results demonstrated that the robot had accurate polishing force based on the online admittance controller with gravity compensation. It also showed a precise proportional uniformity of removal depths at the different normal forces of 10, 15, and 20 N. The final results indicated that the proposed experimental polishing approach is accurate and polishes complex surfaces effectively

A High-precision Current Sense Circuit with Trimming for DC-DC Converts

A high-precision current sense circuit with trimming is proposed to realize the over-current protection of the power management chip and improve its conversion efficiency. Based on solving the problem of voltage offset and current inrush caused by process deviation, this circuit can detect the value of the inductor current accurately. By designing the bandgap reference circuit and the reference voltage bias network, the required stable reference voltage and bias current can be obtained. The trimming bit selection circuit can realize the trimming function. This circuit is designed with TSMC 180nm 1P3M GEN2 process, and all circuits are verified by Cadence Spectre