For coping with the multiple target tracking in the presence of complex time-varying environments and unknown target information, a time resource management scheme based on chance-constraint programming（CCP） employi...For coping with the multiple target tracking in the presence of complex time-varying environments and unknown target information, a time resource management scheme based on chance-constraint programming（CCP） employing fuzzy logic priority is proposed for opportunistic array radar（OAR）. In this scheme,the total beam illuminating time is minimized by effective time resource allocation so that the desired tracking performance is achieved. Meanwhile, owing to the randomness of radar cross section（RCS）, the CCP is used to balance tracking accuracy and time resource conditioned on the specified confidence level. The adaptive fuzzy logic prioritization, imitating the human decision-making process for ranking radar targets, can realize the full potential of radar. The Bayesian Crame ′r-Rao lower bound（BCRLB） provides us with a low bound of localization estimation root-mean-square error（RMSE）, and equally important, it can be calculated predictively. Consequently, it is employed as an optimization criterion for the time resource allocation scheme. The stochastic simulation is integrated into the genetic algorithm（GA） to compose a hybrid intelligent optimization algorithm to solve the CCP optimization problem. The simulation results show that the time resource is saved strikingly and the radar performance is also improved.展开更多
In this paper a square wavelet thresholding method is proposed and evaluated as compared to the other classical wavelet thresholding methods (like soft and hard). The main advantage of this work is to design and imple...In this paper a square wavelet thresholding method is proposed and evaluated as compared to the other classical wavelet thresholding methods (like soft and hard). The main advantage of this work is to design and implement a new wavelet thresholding method and evaluate it against other classical wavelet thresholding methods and hence search for the optimal wavelet mother function among the wide families with a suitable level of decomposition and followed by a novel thresholding method among the existing methods. This optimized method will be used to shrink the wavelet coefficients and yield an adequate compressed pressure signal prior to transmit it. While a comparison evaluation analysis is established, A new proposed procedure is used to compress a synthetic signal and obtain the optimal results through minimization the signal memory size and its transmission bandwidth. There are different performance indices to establish the comparison and evaluation process for signal compression;but the most well-known measuring scores are: NMSE, ESNR, and PDR. The obtained results showed the dominant of the square wavelet thresholding method against other methods using different measuring scores and hence the conclusion by the way for adopting this proposed novel wavelet thresholding method for 1D signal compression in future researches.展开更多
目的利用360°全方向24和36声源测试设备,初步探讨健听中青年和健听老年前期-老年人水平声源定位特点。方法选取2021年4月至2021年9月中国人民解放军总医院耳鼻喉科收治的43例健听成年受试者为研究对象,其中男性22例,女性21例;根据...目的利用360°全方向24和36声源测试设备,初步探讨健听中青年和健听老年前期-老年人水平声源定位特点。方法选取2021年4月至2021年9月中国人民解放军总医院耳鼻喉科收治的43例健听成年受试者为研究对象,其中男性22例,女性21例;根据年龄分为中青年组(21~49岁)20例和老年前期-老年组(50~72岁)23例。两组分别给予纯音听阈测试、全方向24声源(间隔15°)和36声源(间隔10°)水平声源定位(sound localization,SL)能力评估。给声强度60 dB HL,给声刺激为1 kHz啭音,通过计算均方根误差(root mean square,RMS)、平均绝对误差(mean absolutely error,MAE)等评估受试者的声源定位能力。结果24声源老年前期-老年组MAE、RMS均值高于中青年组的MAE、RMS均值,差异有统计学意义(P<0.05);36声源老年前期-老年组MAE、RMS高于中青年组的MAE、RMS,差异无统计学意义(P>0.05)。24声源和36声源前场MAE和RMS均高于后场的MAE和RMS,前后场的MAE和RMS比较,差异有统计学意义(P<0.01);左右场的MAE、RMS比较,差异无统计学意义(P>0.05)。24声源前后混淆比例为7.73%,36声源前后混淆比例为15.42%;24声源和36声源均为正前方的声源定位准确度最差;老年前期-老年组前后混淆的比例高于中青年组,差异无统计学意义(P>0.05)。结论健听老年前期-老年人全方向24声源和36声源水平定位能力,相比健听中青年组有所下降。左右场的定位准确度高,前后场的定位准确度低,正前方定位准确度最低。全方向水平声源定位能力的测试结果与扬声器数量有关,且反应趋势具有一致性。展开更多
针对无迹卡尔曼滤波(unscented Kalman filter,UKF)算法估计锂电池荷电状态(state of charge,SOC)时精度低、稳定性差、产生的sigma点过多导致计算难度大等不足,提出一种基于自适应球形不敏变换方式的无迹卡尔曼滤波(unscented Kalman f...针对无迹卡尔曼滤波(unscented Kalman filter,UKF)算法估计锂电池荷电状态(state of charge,SOC)时精度低、稳定性差、产生的sigma点过多导致计算难度大等不足,提出一种基于自适应球形不敏变换方式的无迹卡尔曼滤波(unscented Kalman filter based on adaptive spherical insensitive transformation,ASIT-UKF)算法。该算法通过使用球形不敏变换方式选择权系数以及初始化一元向量对sigma点的产生进行选取。与UKF算法相比,ASIT-UKF算法产生的sigma点减少近50%,使得算法的计算复杂度大大降低。同时,将产生的所有sigma点进行单位球形面上的归一化处理,提高了数值的稳定性。考虑到实际运行中锂电池系统噪声干扰带来的不确定性,加入Sage-Husa自适应滤波器对不确定性噪声的干扰进行实时更新和修正,以达到提高在线锂电池SOC估计精度的目的。最后,将均方根误差和最大绝对误差计算公式引入到性能估计指标中。实验结果表明,ASIT-UKF算法在准确度、鲁棒性和收敛性方面具有优越的性能。展开更多
基金supported by the National Natural Science Foundation of China(6127132761671241)
文摘For coping with the multiple target tracking in the presence of complex time-varying environments and unknown target information, a time resource management scheme based on chance-constraint programming（CCP） employing fuzzy logic priority is proposed for opportunistic array radar（OAR）. In this scheme,the total beam illuminating time is minimized by effective time resource allocation so that the desired tracking performance is achieved. Meanwhile, owing to the randomness of radar cross section（RCS）, the CCP is used to balance tracking accuracy and time resource conditioned on the specified confidence level. The adaptive fuzzy logic prioritization, imitating the human decision-making process for ranking radar targets, can realize the full potential of radar. The Bayesian Crame ′r-Rao lower bound（BCRLB） provides us with a low bound of localization estimation root-mean-square error（RMSE）, and equally important, it can be calculated predictively. Consequently, it is employed as an optimization criterion for the time resource allocation scheme. The stochastic simulation is integrated into the genetic algorithm（GA） to compose a hybrid intelligent optimization algorithm to solve the CCP optimization problem. The simulation results show that the time resource is saved strikingly and the radar performance is also improved.
文摘In this paper a square wavelet thresholding method is proposed and evaluated as compared to the other classical wavelet thresholding methods (like soft and hard). The main advantage of this work is to design and implement a new wavelet thresholding method and evaluate it against other classical wavelet thresholding methods and hence search for the optimal wavelet mother function among the wide families with a suitable level of decomposition and followed by a novel thresholding method among the existing methods. This optimized method will be used to shrink the wavelet coefficients and yield an adequate compressed pressure signal prior to transmit it. While a comparison evaluation analysis is established, A new proposed procedure is used to compress a synthetic signal and obtain the optimal results through minimization the signal memory size and its transmission bandwidth. There are different performance indices to establish the comparison and evaluation process for signal compression;but the most well-known measuring scores are: NMSE, ESNR, and PDR. The obtained results showed the dominant of the square wavelet thresholding method against other methods using different measuring scores and hence the conclusion by the way for adopting this proposed novel wavelet thresholding method for 1D signal compression in future researches.
文摘目的利用360°全方向24和36声源测试设备,初步探讨健听中青年和健听老年前期-老年人水平声源定位特点。方法选取2021年4月至2021年9月中国人民解放军总医院耳鼻喉科收治的43例健听成年受试者为研究对象,其中男性22例,女性21例;根据年龄分为中青年组(21~49岁)20例和老年前期-老年组(50~72岁)23例。两组分别给予纯音听阈测试、全方向24声源(间隔15°)和36声源(间隔10°)水平声源定位(sound localization,SL)能力评估。给声强度60 dB HL,给声刺激为1 kHz啭音,通过计算均方根误差(root mean square,RMS)、平均绝对误差(mean absolutely error,MAE)等评估受试者的声源定位能力。结果24声源老年前期-老年组MAE、RMS均值高于中青年组的MAE、RMS均值,差异有统计学意义(P<0.05);36声源老年前期-老年组MAE、RMS高于中青年组的MAE、RMS,差异无统计学意义(P>0.05)。24声源和36声源前场MAE和RMS均高于后场的MAE和RMS,前后场的MAE和RMS比较,差异有统计学意义(P<0.01);左右场的MAE、RMS比较,差异无统计学意义(P>0.05)。24声源前后混淆比例为7.73%,36声源前后混淆比例为15.42%;24声源和36声源均为正前方的声源定位准确度最差;老年前期-老年组前后混淆的比例高于中青年组,差异无统计学意义(P>0.05)。结论健听老年前期-老年人全方向24声源和36声源水平定位能力,相比健听中青年组有所下降。左右场的定位准确度高,前后场的定位准确度低,正前方定位准确度最低。全方向水平声源定位能力的测试结果与扬声器数量有关,且反应趋势具有一致性。
文摘针对无迹卡尔曼滤波(unscented Kalman filter,UKF)算法估计锂电池荷电状态(state of charge,SOC)时精度低、稳定性差、产生的sigma点过多导致计算难度大等不足,提出一种基于自适应球形不敏变换方式的无迹卡尔曼滤波(unscented Kalman filter based on adaptive spherical insensitive transformation,ASIT-UKF)算法。该算法通过使用球形不敏变换方式选择权系数以及初始化一元向量对sigma点的产生进行选取。与UKF算法相比,ASIT-UKF算法产生的sigma点减少近50%,使得算法的计算复杂度大大降低。同时,将产生的所有sigma点进行单位球形面上的归一化处理,提高了数值的稳定性。考虑到实际运行中锂电池系统噪声干扰带来的不确定性,加入Sage-Husa自适应滤波器对不确定性噪声的干扰进行实时更新和修正,以达到提高在线锂电池SOC估计精度的目的。最后,将均方根误差和最大绝对误差计算公式引入到性能估计指标中。实验结果表明,ASIT-UKF算法在准确度、鲁棒性和收敛性方面具有优越的性能。
