Long term integration algorithm for high-dynamic targets

A new long term integration algorithm is proposed forhigh-dynamic targets, which can resolve the problems of spectrumspread, frequency walk and pseudorandom noise （PRN）code phase curvature caused by the motion of targets. This algorithmfirst applies a keystone transform based improved discretepolynomial-phase transform （KT-IDPT） to estimate the Dopplerchirp rate. Then, based on the estimated Doppler chirp rate,dechirping and envelope translation are performed on the partialcorrelation results to correct the spectrum spread and the codephase curvature. The simulation results demonstrate that the proposedmethod has low integration loss and computational burden.

Two-step compressed acquisition method for Doppler frequency and Doppler rate estimation in high-dynamic and weak signal environments

To acquire global navigation satellite system(GNSS)signals means four-dimension acquisition of bit transition,Doppler frequency,Doppler rate,and code phase in high-dynamic and weak signal environments,which needs a high computational cost.To reduce the computations,this paper proposes a twostep compressed acquisition method(TCAM)for the post-correlation signal parameters estimation.Compared with the fast Fourier transform(FFT)based methods,TCAM uses fewer frequency search points.In this way,the proposed method reduces complex multiplications,and uses real multiplications instead of improving the accuracy of the Doppler frequency and the Doppler rate.Furthermore,the differential process between two adjacent milliseconds is used for avoiding the impact of bit transition and the Doppler frequency on the integration peak.The results demonstrate that due to the reduction of complex multiplications,the computational cost of TCAM is lower than that of the FFT based method under the same signal to noise ratio(SNR).

A fine acquisition algorithm based on fast three-time FRFT for dynamic and weak GNSS signals

As high-dynamics and weak-signal are of two primary concerns of navigation using Global Navigation Satellite System(GNSS)signals,an acquisition algorithm based on threetime fractional Fourier transform(FRFT)is presented to simplify the calculation effectively.Firstly,the correlation results similar to linear frequency modulated(LFM)signals are derived on the basis of the high dynamic GNSS signal model.Then,the principle of obtaining the optimum rotation angle is analyzed,which is measured by FRFT projection lengths with two selected rotation angles.Finally,Doppler shift,Doppler rate,and code phase are accurately estimated in a real-time and low signal to noise ratio(SNR)wireless communication system.The theoretical analysis and simulation results show that the fast FRFT algorithm can accurately estimate the high dynamic parameters by converting the traditional two-dimensional search process to only three times FRFT.While the acquisition performance is basically the same,the computational complexity and running time are greatly reduced,which is more conductive to practical application.

高动态范围电视系统技术漫谈

超高清电视是当下电视发展的重要方向,高动态范围(HDR)是超高清电视的一项关键技术,涉及端到端的技术和产业实现。本文简要概括了高动态范围HDR内容采集、传输、显示的关键技术点,并梳理了国际上主要标准化体系下技术的进展情况。

Perception-Driven Learning of High-Dynamic Jumping Motions for Single-Legged Robots

Legged robots show great potential for high-dynamic motions in continuous interaction with the physical environment,yet achieving animal-like agility remains significant challenges.Legged animals usually predict and plan their next locomotion by combining high-dimensional information from proprioception and exteroception,and adjust the stiffness of the body’s skeletal muscle system to adapt to the current environment.Traditional control methods have limitations in handling high-dimensional state information or complex robot motion that are difficult to plan manually,and Deep Reinforcement Learning(DRL)algorithms provide new solutions to robot motioncontrol problems.Inspired by biomimetics theory,we propose a perception-driven high-dynamic jump adaptive learning algorithm by combining DRL algorithms with Virtual Model Control(VMC)method.The robot will be fully trained in simulation to explore its motion potential by learning the factors related to continuous jumping while knowing its real-time jumping height.The policy trained in simulation is successfully deployed on the bio-inspired single-legged robot testing platform without further adjustments.Experimental results show that the robot can achieve continuous and ideal vertical jumping motion through simple training.

Multiscale structural analysis inspired by exceptional load cases concerning the immersed tunnel of the Hong Kong-Zhuhai-Macao Bridge

This paper contains an assessment of the added value of multiscale material models for concrete in the context of macroscopic struc-tural analysis of(steel-reinforced)concrete structures.Two examples are discussed.They are inspired by the possibility of car accidents inside the immersed tunnel of the Hong Kong-Zhuhai-Macao Bridge(HZMB).The first example deals with vehicles crashing into the tunnel wall.The high-dynamic strengthening effect of concrete is studied based on an engineering mechanics model.The structural nature of the dynamic strength increase factor(DIF)is demonstrated by means of high-dynamic strength values measured on mortar cylinders of different size.Furthermore,the evolution of the DIF as a function of hardening of concrete at material ages beyond 28 days is studied.A validated multiscale model for concrete renders a customized analysis for the specific concrete used for the aforementioned tunnel possible.It is found that the DIF decreases with progressive hardening of concrete at material ages beyond 28 days.The second example is inspired by tunnel fires as may happen after car accidents.The study refers to thermal stresses in steel-reinforced concrete beams sub-jected to sudden heating.The thermal expansion coefficient of the concrete of the tunnel is quantified by means of a multiscale model.It is used as input for linear thermo-mechanical Finite-Element simulations of steel-reinforced concrete beams.The essential macroscopic simulation results are temperature distributions and associated stress fields.They are employed for top-down quantification of micro-scopic stress states inside the cement paste and the aggregates.This allows for quantifying two sources of microstructural stress fluctu-ations:(i)the macro-to-micro stress concentration and(ii)the mismatch of microscopic thermal expansion coefficients.In both examples,the multiscale models for concrete have increased the informative content of the structural simulations.