Path planning is crucial for autonomous flight of fixed-wing Unmanned Aerial Vehicles(UAVs).However,due to the high-speed flight and complex control of fixed-wing UAVs,ensuring the feasibility and safety of planned pa...Path planning is crucial for autonomous flight of fixed-wing Unmanned Aerial Vehicles(UAVs).However,due to the high-speed flight and complex control of fixed-wing UAVs,ensuring the feasibility and safety of planned paths in complex environments is challenging.This paper proposes a feasible path planning algorithm named Closed-loop Radial Ray A*(CL-RaA*).The core components of the CL-RaA*include an adaptive variable-step-size path search and a just-in-time expansion primitive.The former enables fast path search in complex environments,while the latter ensures the feasibility of the generated paths.By integrating these two components and conducting safety checks on the trajectories to be expanded,the CL-RaA*can rapidly generate safe and feasible paths that satisfy the differential constraints that comprehensively consider the dynamics and control characteristics of six-degree-of-freedom fixed-wing UAVs.The final performance tests and simulation validations demonstrate that the CL-RaA*can generate safe and feasible paths in various environments.Compared to feasible path planning algorithms that use the rapidlyexploring random trees,the CL-RaA*not only ensures deterministic planning results in the same scenarios but also generates smoother feasible paths for fixed-wing UAVs more efficiently.In environments with dense grid obstacles,the feasible paths generated by the CL-RaA*are more conducive to UAV tracking compared to those planned using Dubins curves.展开更多
Nano-volt magnetic resonance sounding(MRS) signals are sufficiently weak so that during the actual measurement, they are affected by environmental electromagnetic noise, leading to inaccuracy of the extracted characte...Nano-volt magnetic resonance sounding(MRS) signals are sufficiently weak so that during the actual measurement, they are affected by environmental electromagnetic noise, leading to inaccuracy of the extracted characteristic parameters and hindering effective inverse interpretation. Considering the complexity and non-homogeneous spatial distribution of environmental noise and based on the theory of adaptive noise cancellation, a model system for noise cancellation using multi-reference coils was constructed to receive MRS signals. The feasibility of this system with theoretical calculation and experiments was analyzed and a modified sigmoid variable step size least mean square(SVSLMS) algorithm for noise cancellation was presented. The simulation results show that, the multi-reference coil method performs better than the single one on both signal-to-noise ratio(SNR) improvement and signal waveform optimization after filtering, under the condition of different noise correlations in the reference coils and primary detecting coils and different SNRs. In particular, when the noise correlation is poor and the SNR<0, the SNR can be improved by more than 8 dB after filtering with multi-reference coils. And the average fitting errors for initial amplitude and relaxation time are within 5%. Compared with the normalized least mean square(NLMS) algorithm and multichannel Wiener filter and processing field test data, the effectiveness of the proposed method is verified.展开更多
By analyzing algorithms available for variable step size least mean square(LMS)adaptive filter,a new modified LMS adaptive filtering algorithm with variable step size is proposed,along with performance analysis based ...By analyzing algorithms available for variable step size least mean square(LMS)adaptive filter,a new modified LMS adaptive filtering algorithm with variable step size is proposed,along with performance analysis based on different parameters.Compared with the existing algorithms through the simulation,the proposed algorithm has faster convergence speed and smaller steady state error.展开更多
The problem of inter symbol interference( ISI) in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn't require a ...The problem of inter symbol interference( ISI) in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn't require a training sequence,a blind equalization channel is implemented in the receiver to increase the throughput of the system. To improve the performances of both the blind equalizer and the system,a joint receiving mechanismincluding variable step size( VSS) modified constant modulus algorithms( MC-MA) and modified decision directed modulus algorithms( MD DMA) is proposed to ameliorate the convergence speed and mean square error( MSE) performance and combat the phase error when using high order QAM modulation. The VSS scheme is based on the selection of step size according to the distance between the output of the equalizer and the desired output in the constellation plane. Analysis and simulations showthat the performance of the proposed VSS-MCMA-MD DMA mechanismis better than that of algorithms with a fixed step size. In addition,the MCMA-MDDMA with VSS can performthe phase recovery by itself.展开更多
This paper puts forward a new variable step size LMS adaptive algorithm based on variable region. The step size p(k) in the algorithm varies with the variation of the region of deviation e (k) to ensure the optimi...This paper puts forward a new variable step size LMS adaptive algorithm based on variable region. The step size p(k) in the algorithm varies with the variation of the region of deviation e (k) to ensure the optimization of the three performance objectives including initial convergent speed, trace ability of the time-varying system and steady disregulation. The paper demonstrates the convergence of the algorithm accompanied by random noise,展开更多
The contradiction of variable step size least mean square(LMS)algorithm between fast convergence speed and small steady-state error has always existed.So,a new algorithm based on the combination of logarithmic and sym...The contradiction of variable step size least mean square(LMS)algorithm between fast convergence speed and small steady-state error has always existed.So,a new algorithm based on the combination of logarithmic and symbolic function and step size factor is proposed.It establishes a new updating method of step factor that is related to step factor and error signal.This work makes an analysis from 3 aspects:theoretical analysis,theoretical verification and specific experiments.The experimental results show that the proposed algorithm is superior to other variable step size algorithms in convergence speed and steady-state error.展开更多
Forward modeling of elastic wave propagation in porous media has great importance for understanding and interpreting the influences of rock properties on characteristics of seismic wavefield. However,the finite-differ...Forward modeling of elastic wave propagation in porous media has great importance for understanding and interpreting the influences of rock properties on characteristics of seismic wavefield. However,the finite-difference forward-modeling method is usually implemented with global spatial grid-size and time-step; it consumes large amounts of computational cost when small-scaled oil/gas-bearing structures or large velocity-contrast exist underground. To overcome this handicap,combined with variable grid-size and time-step,this paper developed a staggered-grid finite-difference scheme for elastic wave modeling in porous media. Variable finite-difference coefficients and wavefield interpolation were used to realize the transition of wave propagation between regions of different grid-size. The accuracy and efficiency of the algorithm were shown by numerical examples. The proposed method is advanced with low computational cost in elastic wave simulation for heterogeneous oil/gas reservoirs.展开更多
In order to improve the problem that the filtered-x least mean square(FxLMS)algorithm cannot take into account the convergence speed,steady-state error during active noise control.A piecewise variable step size FxLMS ...In order to improve the problem that the filtered-x least mean square(FxLMS)algorithm cannot take into account the convergence speed,steady-state error during active noise control.A piecewise variable step size FxLMS algorithm based on logarithmic function(PLFxLMS)is proposed,and the genetic algorithm are introduced to optimize the parameters of logarithmic variable step size FxLMS(LFxLMS),improved logarithmic variable step size Films(IFxLMS),and PLFxLMS algorithms.Bandlimited white noise is used as the input signal,FxLMS,LFxLMS,ILFxLMS,and PLFxLMS algorithms are used to conduct active noise control simulation,and the convergence speed and steady-state characteristic of four algorithms are comparatively analyzed.Compared with the other three algorithms,the PLFxLMS algorithm proposed in this paper has the fastest convergence speed,and small steady-state error.The PLFxLMS algorithm can effectively improve the convergence speed and steady-state error of the FxLMS algorithm that cannot be controlled at the same time,and achieve the optimal effect.展开更多
雷达等大功率脉冲负载(pulsed power load,PPL)接入船舶综合电力系统,导致低惯量系统出现周期性冲击振荡,其非线性周期时变特征加剧了系统响应的不确定性,进而导致系统暂态越限甚至失稳。为分析系统非线性周期时变特征及动态行为,明晰...雷达等大功率脉冲负载(pulsed power load,PPL)接入船舶综合电力系统,导致低惯量系统出现周期性冲击振荡,其非线性周期时变特征加剧了系统响应的不确定性,进而导致系统暂态越限甚至失稳。为分析系统非线性周期时变特征及动态行为,明晰周期扰动的暂态稳定机理,提出暂态功角轨迹与稳定边界计算方法。该方法构建含PPL船舶综合电力系统的变步长变阶数Dormand-Prince解析模型,解决非线性周期时变状态量建模问题,并刻画暂态功角相空间轨迹;构造Lyapunov周期指数作为系统周期时变状态量收敛性的判据,提取状态轨迹特征并辨识系统参数的收敛稳定、亚稳定及发散失稳区域边界。以该判据为基础,提出参数灵敏度计算方法,量化分析系统暂态现象多时间尺度参量特征。利用RT-LAB平台建立含脉冲负载的典型船舶综合电力系统模型,仿真结果表明所提方法能够精确判断船舶综合电力系统稳定状态,且暂态稳定边界的误差约为4%。展开更多
针对RRT(Rapidly-exploring Random Tree)算法在机器人路径规划过程存在采样点随机性高、算法效率低、路径规划时间长以及规划路径冗长等问题,文中提出一种结合人工势场法的双向RRT路径规划算法。将传统RRT算法中单向扩展方式改为由起...针对RRT(Rapidly-exploring Random Tree)算法在机器人路径规划过程存在采样点随机性高、算法效率低、路径规划时间长以及规划路径冗长等问题,文中提出一种结合人工势场法的双向RRT路径规划算法。将传统RRT算法中单向扩展方式改为由起点和终点同时进行扩展,在节点扩展时加入人工势场法进行引导,增加节点扩展的目的性。将固定步长改换为可变步长,使随机树可以更快地向目标点扩展。对生成路径进行剪枝处理,删除路径中的冗余节点,进一步缩短路径长度。利用MATLAB仿真平台在相同环境下对比所提改进算法与RRT-Connect算法、DRRT-Connect(Dynamic Rapidly-exploring Random Tree Connect)算法、GB(Goal-Biased)-RRT算法、A*算法、PRM(Probabilistic Road Map)算法的路径规划效果。仿真结果表明,所提改进算法与其他改进算法相比最短路径缩短了7%,最短搜索时间降低了65%,提高了算法的规划效率。将所提算法应用于机器人,结果证明了其具有较强可行性。展开更多
在实际的自适应滤波系统中普遍存在随机处理延迟和异质测量噪声(如高斯噪声、脉冲噪声等)的问题,而现有的变步长最小均方误差(Variable Step-Size Least Mean Square,VSSLMS)算法在分析时通常假设系统为无延时系统.为了解决上述问题,提...在实际的自适应滤波系统中普遍存在随机处理延迟和异质测量噪声(如高斯噪声、脉冲噪声等)的问题,而现有的变步长最小均方误差(Variable Step-Size Least Mean Square,VSSLMS)算法在分析时通常假设系统为无延时系统.为了解决上述问题,提出一种随机延迟容忍的鲁棒VSSLMS算法,利用Squareplus函数的两个优势:(1)在时延条件下对梯度估计稳定性具有固有平滑性;(2)针对多种类型分布的非线性干扰具有抑制能力.在理论上分析该算法的均方误差和稳态均方误差以评估其性能,并设计系统辨识实验仿真来验证该算法的有效性,且结果与理论分析一致,也优于现有的自适应滤波算法.因此提出的算法不仅表现出更好的稳态性能,在对抗随机时延和多类型测量噪声时也具有更好的鲁棒性.展开更多
基金supported by the National Natural Science Foundation of China(No.52272382)the Fundamental Research Funds for the Central Universities,China。
摘要Path planning is crucial for autonomous flight of fixed-wing Unmanned Aerial Vehicles(UAVs).However,due to the high-speed flight and complex control of fixed-wing UAVs,ensuring the feasibility and safety of planned paths in complex environments is challenging.This paper proposes a feasible path planning algorithm named Closed-loop Radial Ray A*(CL-RaA*).The core components of the CL-RaA*include an adaptive variable-step-size path search and a just-in-time expansion primitive.The former enables fast path search in complex environments,while the latter ensures the feasibility of the generated paths.By integrating these two components and conducting safety checks on the trajectories to be expanded,the CL-RaA*can rapidly generate safe and feasible paths that satisfy the differential constraints that comprehensively consider the dynamics and control characteristics of six-degree-of-freedom fixed-wing UAVs.The final performance tests and simulation validations demonstrate that the CL-RaA*can generate safe and feasible paths in various environments.Compared to feasible path planning algorithms that use the rapidlyexploring random trees,the CL-RaA*not only ensures deterministic planning results in the same scenarios but also generates smoother feasible paths for fixed-wing UAVs more efficiently.In environments with dense grid obstacles,the feasible paths generated by the CL-RaA*are more conducive to UAV tracking compared to those planned using Dubins curves.
基金Projects(41204079,41504086)supported by the National Natural Science Foundation of ChinaProject(20160101281JC)supported by the Natural Science Foundation of Jilin Province,ChinaProjects(2016M590258,2015T80301)supported by the Postdoctoral Science Foundation of China
摘要Nano-volt magnetic resonance sounding(MRS) signals are sufficiently weak so that during the actual measurement, they are affected by environmental electromagnetic noise, leading to inaccuracy of the extracted characteristic parameters and hindering effective inverse interpretation. Considering the complexity and non-homogeneous spatial distribution of environmental noise and based on the theory of adaptive noise cancellation, a model system for noise cancellation using multi-reference coils was constructed to receive MRS signals. The feasibility of this system with theoretical calculation and experiments was analyzed and a modified sigmoid variable step size least mean square(SVSLMS) algorithm for noise cancellation was presented. The simulation results show that, the multi-reference coil method performs better than the single one on both signal-to-noise ratio(SNR) improvement and signal waveform optimization after filtering, under the condition of different noise correlations in the reference coils and primary detecting coils and different SNRs. In particular, when the noise correlation is poor and the SNR<0, the SNR can be improved by more than 8 dB after filtering with multi-reference coils. And the average fitting errors for initial amplitude and relaxation time are within 5%. Compared with the normalized least mean square(NLMS) algorithm and multichannel Wiener filter and processing field test data, the effectiveness of the proposed method is verified.
基金Natural Science Foundation of Shandong Province of China(No.ZR2012FM011)Shandong University of Science and Technology Research Fund(No.2010KYTD101)
摘要By analyzing algorithms available for variable step size least mean square(LMS)adaptive filter,a new modified LMS adaptive filtering algorithm with variable step size is proposed,along with performance analysis based on different parameters.Compared with the existing algorithms through the simulation,the proposed algorithm has faster convergence speed and smaller steady state error.
基金Supported by the National Natural Science Foundation of China(6100201461101129+1 种基金6122700161072050)
摘要The problem of inter symbol interference( ISI) in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn't require a training sequence,a blind equalization channel is implemented in the receiver to increase the throughput of the system. To improve the performances of both the blind equalizer and the system,a joint receiving mechanismincluding variable step size( VSS) modified constant modulus algorithms( MC-MA) and modified decision directed modulus algorithms( MD DMA) is proposed to ameliorate the convergence speed and mean square error( MSE) performance and combat the phase error when using high order QAM modulation. The VSS scheme is based on the selection of step size according to the distance between the output of the equalizer and the desired output in the constellation plane. Analysis and simulations showthat the performance of the proposed VSS-MCMA-MD DMA mechanismis better than that of algorithms with a fixed step size. In addition,the MCMA-MDDMA with VSS can performthe phase recovery by itself.
基金Supported by Natural Science Foundation of Beijing of China (No.2005AA501140)
摘要This paper puts forward a new variable step size LMS adaptive algorithm based on variable region. The step size p(k) in the algorithm varies with the variation of the region of deviation e (k) to ensure the optimization of the three performance objectives including initial convergent speed, trace ability of the time-varying system and steady disregulation. The paper demonstrates the convergence of the algorithm accompanied by random noise,
基金the National Natural Science Foundation of China(No.51575328,61503232).
摘要The contradiction of variable step size least mean square(LMS)algorithm between fast convergence speed and small steady-state error has always existed.So,a new algorithm based on the combination of logarithmic and symbolic function and step size factor is proposed.It establishes a new updating method of step factor that is related to step factor and error signal.This work makes an analysis from 3 aspects:theoretical analysis,theoretical verification and specific experiments.The experimental results show that the proposed algorithm is superior to other variable step size algorithms in convergence speed and steady-state error.
基金supported by the National Basic Research Program of China (No. 2013CB228604)the National Science and Technology Major Project (No. 2011ZX05030-004-002,2011ZX05019-003)the National Natural Science Foundation (No. 41004050)
摘要Forward modeling of elastic wave propagation in porous media has great importance for understanding and interpreting the influences of rock properties on characteristics of seismic wavefield. However,the finite-difference forward-modeling method is usually implemented with global spatial grid-size and time-step; it consumes large amounts of computational cost when small-scaled oil/gas-bearing structures or large velocity-contrast exist underground. To overcome this handicap,combined with variable grid-size and time-step,this paper developed a staggered-grid finite-difference scheme for elastic wave modeling in porous media. Variable finite-difference coefficients and wavefield interpolation were used to realize the transition of wave propagation between regions of different grid-size. The accuracy and efficiency of the algorithm were shown by numerical examples. The proposed method is advanced with low computational cost in elastic wave simulation for heterogeneous oil/gas reservoirs.
摘要In order to improve the problem that the filtered-x least mean square(FxLMS)algorithm cannot take into account the convergence speed,steady-state error during active noise control.A piecewise variable step size FxLMS algorithm based on logarithmic function(PLFxLMS)is proposed,and the genetic algorithm are introduced to optimize the parameters of logarithmic variable step size FxLMS(LFxLMS),improved logarithmic variable step size Films(IFxLMS),and PLFxLMS algorithms.Bandlimited white noise is used as the input signal,FxLMS,LFxLMS,ILFxLMS,and PLFxLMS algorithms are used to conduct active noise control simulation,and the convergence speed and steady-state characteristic of four algorithms are comparatively analyzed.Compared with the other three algorithms,the PLFxLMS algorithm proposed in this paper has the fastest convergence speed,and small steady-state error.The PLFxLMS algorithm can effectively improve the convergence speed and steady-state error of the FxLMS algorithm that cannot be controlled at the same time,and achieve the optimal effect.
摘要雷达等大功率脉冲负载(pulsed power load,PPL)接入船舶综合电力系统,导致低惯量系统出现周期性冲击振荡,其非线性周期时变特征加剧了系统响应的不确定性,进而导致系统暂态越限甚至失稳。为分析系统非线性周期时变特征及动态行为,明晰周期扰动的暂态稳定机理,提出暂态功角轨迹与稳定边界计算方法。该方法构建含PPL船舶综合电力系统的变步长变阶数Dormand-Prince解析模型,解决非线性周期时变状态量建模问题,并刻画暂态功角相空间轨迹;构造Lyapunov周期指数作为系统周期时变状态量收敛性的判据,提取状态轨迹特征并辨识系统参数的收敛稳定、亚稳定及发散失稳区域边界。以该判据为基础,提出参数灵敏度计算方法,量化分析系统暂态现象多时间尺度参量特征。利用RT-LAB平台建立含脉冲负载的典型船舶综合电力系统模型,仿真结果表明所提方法能够精确判断船舶综合电力系统稳定状态,且暂态稳定边界的误差约为4%。
摘要针对RRT(Rapidly-exploring Random Tree)算法在机器人路径规划过程存在采样点随机性高、算法效率低、路径规划时间长以及规划路径冗长等问题,文中提出一种结合人工势场法的双向RRT路径规划算法。将传统RRT算法中单向扩展方式改为由起点和终点同时进行扩展,在节点扩展时加入人工势场法进行引导,增加节点扩展的目的性。将固定步长改换为可变步长,使随机树可以更快地向目标点扩展。对生成路径进行剪枝处理,删除路径中的冗余节点,进一步缩短路径长度。利用MATLAB仿真平台在相同环境下对比所提改进算法与RRT-Connect算法、DRRT-Connect(Dynamic Rapidly-exploring Random Tree Connect)算法、GB(Goal-Biased)-RRT算法、A*算法、PRM(Probabilistic Road Map)算法的路径规划效果。仿真结果表明,所提改进算法与其他改进算法相比最短路径缩短了7%,最短搜索时间降低了65%,提高了算法的规划效率。将所提算法应用于机器人,结果证明了其具有较强可行性。
摘要在实际的自适应滤波系统中普遍存在随机处理延迟和异质测量噪声(如高斯噪声、脉冲噪声等)的问题,而现有的变步长最小均方误差(Variable Step-Size Least Mean Square,VSSLMS)算法在分析时通常假设系统为无延时系统.为了解决上述问题,提出一种随机延迟容忍的鲁棒VSSLMS算法,利用Squareplus函数的两个优势:(1)在时延条件下对梯度估计稳定性具有固有平滑性;(2)针对多种类型分布的非线性干扰具有抑制能力.在理论上分析该算法的均方误差和稳态均方误差以评估其性能,并设计系统辨识实验仿真来验证该算法的有效性,且结果与理论分析一致,也优于现有的自适应滤波算法.因此提出的算法不仅表现出更好的稳态性能,在对抗随机时延和多类型测量噪声时也具有更好的鲁棒性.