A high-accuracy,low-dropout （LDO） voltage regulator is presented. Using the slow-rolloff frequency compensation scheme, the LDO effectively overcomes the stability problem, facilitates the use of a ceramic capacitor...A high-accuracy,low-dropout （LDO） voltage regulator is presented. Using the slow-rolloff frequency compensation scheme, the LDO effectively overcomes the stability problem, facilitates the use of a ceramic capacitor, and improves the output voltage accuracy, which is critical for powering high-performance analog circuitry. The slow-rolloff compensation scheme is realized by introducing three pole-zero pairs, including the proposed polezero pair and sense zero. The post-layout simulation results demonstrate that this LDO has robust system stability, a high open-loop gain, and a high unit-gain frequency,which lead to excellent regulation and transient response performance. The line and load regulation are 27μV/V and 3.78μV/mA, and the overshoots of the output voltage are less than 30mV,while the dropout voltage is 120mV for a 150mA load current.展开更多
As a typical implementation of the probability hypothesis density(PHD) filter, sequential Monte Carlo PHD(SMC-PHD) is widely employed in highly nonlinear systems. However, the particle impoverishment problem introduce...As a typical implementation of the probability hypothesis density(PHD) filter, sequential Monte Carlo PHD(SMC-PHD) is widely employed in highly nonlinear systems. However, the particle impoverishment problem introduced by the resampling step, together with the high computational burden problem, may lead to performance degradation and restrain the use of SMC-PHD filter in practical applications. In this work, a novel SMC-PHD filter based on particle compensation is proposed to solve above problems. Firstly, according to a comprehensive analysis on the particle impoverishment problem, a new particle generating mechanism is developed to compensate the particles. Then, all the particles are integrated into the SMC-PHD filter framework. Simulation results demonstrate that, in comparison with the SMC-PHD filter, proposed PC-SMC-PHD filter is capable of overcoming the particle impoverishment problem, as well as improving the processing rate for a certain tracking accuracy in different scenarios.展开更多
文摘A high-accuracy,low-dropout （LDO） voltage regulator is presented. Using the slow-rolloff frequency compensation scheme, the LDO effectively overcomes the stability problem, facilitates the use of a ceramic capacitor, and improves the output voltage accuracy, which is critical for powering high-performance analog circuitry. The slow-rolloff compensation scheme is realized by introducing three pole-zero pairs, including the proposed polezero pair and sense zero. The post-layout simulation results demonstrate that this LDO has robust system stability, a high open-loop gain, and a high unit-gain frequency,which lead to excellent regulation and transient response performance. The line and load regulation are 27μV/V and 3.78μV/mA, and the overshoots of the output voltage are less than 30mV,while the dropout voltage is 120mV for a 150mA load current.
基金Projects(61671462,61471383,61671463,61304103)supported by the National Natural Science Foundation of ChinaProject(ZR2012FQ004)supported by the Natural Science Foundation of Shandong Province,China
文摘As a typical implementation of the probability hypothesis density(PHD) filter, sequential Monte Carlo PHD(SMC-PHD) is widely employed in highly nonlinear systems. However, the particle impoverishment problem introduced by the resampling step, together with the high computational burden problem, may lead to performance degradation and restrain the use of SMC-PHD filter in practical applications. In this work, a novel SMC-PHD filter based on particle compensation is proposed to solve above problems. Firstly, according to a comprehensive analysis on the particle impoverishment problem, a new particle generating mechanism is developed to compensate the particles. Then, all the particles are integrated into the SMC-PHD filter framework. Simulation results demonstrate that, in comparison with the SMC-PHD filter, proposed PC-SMC-PHD filter is capable of overcoming the particle impoverishment problem, as well as improving the processing rate for a certain tracking accuracy in different scenarios.
