For the purpose of resolving the problem of performance deterioration introduced by inaccurate phase compensation in existing coherent averaging line spectrum detectors, a modified coherent detector is proposed. The t...For the purpose of resolving the problem of performance deterioration introduced by inaccurate phase compensation in existing coherent averaging line spectrum detectors, a modified coherent detector is proposed. The three point interpolation in frequency domain is applied to obtain accurate estimate of phase difference between segments when the segmented length is not an integral multiple of the signal period. Then the segmented data are multiplied by a complex coefficient to remove the phase difference and synchronize the phases of all the segments before coherent averaging. Theoretical analysis shows that there will be a gain of 3.9 dB at most by using the modified detector. The detection performance of the incoher- ent averaging power spectrum detector （AVGPR）, the phase coherent averaging detector, the modified coherent averaging detector are compared with each other by computer simulations. The results coincide basically with the theoretical analysis, which show the superiority of the modified detector to the former two detectors.展开更多
Soft fault compensation plays an important role in mobile robot locating, mapping, and navigating. It is difficult to achieve fast and accurate compensation for mobile robots because they are usually highly non-linear...Soft fault compensation plays an important role in mobile robot locating, mapping, and navigating. It is difficult to achieve fast and accurate compensation for mobile robots because they are usually highly non-linear, non-Gaussian systems with limited computation and memory resources. An adaptive particle filter is presented to compensate two kinds of soft faults for mobile robots, i.e., noise or factor faults of dead reckoning sensors and slippage of wheels. Firstly, the kinematics models and the fault models are discussed, and five kinds of residual features are extracted to detect soft faults. Secondly, an adaptive particle filter is designed for fault compensation, and two kinds of adaptive scheme are discussed： 1） the noise variances of linear speed and yaw rate are adjusted according to residual features; 2） the particle number is adapted according to Kullback-Leibler divergence （KLD） of two approximate distribution denoted with two particle sets with different particles, i.e., increasing particle number if the KLD is large and decreasing particle number if the KLD is small. The theoretic proof is given and experimental results show the efficiency and accuracy of the presented approach.展开更多
文摘For the purpose of resolving the problem of performance deterioration introduced by inaccurate phase compensation in existing coherent averaging line spectrum detectors, a modified coherent detector is proposed. The three point interpolation in frequency domain is applied to obtain accurate estimate of phase difference between segments when the segmented length is not an integral multiple of the signal period. Then the segmented data are multiplied by a complex coefficient to remove the phase difference and synchronize the phases of all the segments before coherent averaging. Theoretical analysis shows that there will be a gain of 3.9 dB at most by using the modified detector. The detection performance of the incoher- ent averaging power spectrum detector （AVGPR）, the phase coherent averaging detector, the modified coherent averaging detector are compared with each other by computer simulations. The results coincide basically with the theoretical analysis, which show the superiority of the modified detector to the former two detectors.
基金the National Natural Science Foundation of China (Grant No. 60234030)National Basic Research Project (Grant No. A1420060159)
文摘Soft fault compensation plays an important role in mobile robot locating, mapping, and navigating. It is difficult to achieve fast and accurate compensation for mobile robots because they are usually highly non-linear, non-Gaussian systems with limited computation and memory resources. An adaptive particle filter is presented to compensate two kinds of soft faults for mobile robots, i.e., noise or factor faults of dead reckoning sensors and slippage of wheels. Firstly, the kinematics models and the fault models are discussed, and five kinds of residual features are extracted to detect soft faults. Secondly, an adaptive particle filter is designed for fault compensation, and two kinds of adaptive scheme are discussed： 1） the noise variances of linear speed and yaw rate are adjusted according to residual features; 2） the particle number is adapted according to Kullback-Leibler divergence （KLD） of two approximate distribution denoted with two particle sets with different particles, i.e., increasing particle number if the KLD is large and decreasing particle number if the KLD is small. The theoretic proof is given and experimental results show the efficiency and accuracy of the presented approach.
