To classify the frequency modulation signal, this paper employs a parameter invariant filter, which can transfer the frequency modulated information to variety of its envelope, and then extracts the histogram feature ...To classify the frequency modulation signal, this paper employs a parameter invariant filter, which can transfer the frequency modulated information to variety of its envelope, and then extracts the histogram feature to classify the modulation type. This method can efficiently classify the type of a signal such as frequency modulation （FM）, binary frequency shift keyiing （BFSK）, quadrature frequency shift keying （QFSK）, 8-ary frequency shift keying （8FSK）, etc. It can easily be realized and is especially suitable to applications in software radio.展开更多
A robust finite-horizon Kalman filter is designed for linear discrete-time systems subject to norm-bounded uncertainties in the modeling parameters and missing measurements.The missing measurements were described by a...A robust finite-horizon Kalman filter is designed for linear discrete-time systems subject to norm-bounded uncertainties in the modeling parameters and missing measurements.The missing measurements were described by a binary switching sequence satisfying a conditional probability distribution,the commonest cases in engineering,such that the expectation of the measurements could be utilized during the iteration process.To consider the uncertainties in the system model,an upperbound for the estimation error covariance was obtained since its real value was unaccessible.Our filter scheme is on the basis of minimizing the obtained upper bound where we refer to the deduction of a classic Kalman filter thus calculation of the derivatives are avoided.Simulations are presented to illustrate the effectiveness of the proposed approach.展开更多
Estimating cross-range velocity is a challenging task for space-borne synthetic aperture radar（SAR）, which is important for ground moving target indication（GMTI）. Because the velocity of a target is very small com...Estimating cross-range velocity is a challenging task for space-borne synthetic aperture radar（SAR）, which is important for ground moving target indication（GMTI）. Because the velocity of a target is very small compared with that of the satellite, it is difficult to correctly estimate it using a conventional monostatic platform algorithm. To overcome this problem, a novel method employing multistatic SAR is presented in this letter. The proposed hybrid method, which is based on an extended space-time model（ESTIM） of the azimuth signal, has two steps： first, a set of finite impulse response（FIR） filter banks based on a fractional Fourier transform（FrFT） is used to separate multiple targets within a range gate; second, a cross-correlation spectrum weighted subspace fitting（CSWSF） algorithm is applied to each of the separated signals in order to estimate their respective parameters. As verified through computer simulation with the constellations of Cartwheel, Pendulum and Helix, this proposed time-frequency-subspace method effectively improves the estimation precision of the cross-range velocities of multiple targets.展开更多
Channel friction is an important parameter in hydraulic analysis. A channel friction parameter inversion method based on Kalman Filter with unknown parameter vector is proposed. Numerical simulations indicate that whe...Channel friction is an important parameter in hydraulic analysis. A channel friction parameter inversion method based on Kalman Filter with unknown parameter vector is proposed. Numerical simulations indicate that when the number of monitoring stations exceeds a critical value, the so lution is hardly affected. In addition, Kalman Filter with unknown parameter vector is effective only at unsteady state. For the nonlinear equations, computations of sensitivity matrices are time-costly. Two simplified measures can reduce computing time, but not influence the results. One is to reduce sensitivity matrix analysis time, the other is to substitute for sensitivity matrix.展开更多
基金Project supported by National High-Technology Research and De-velopment Program(Grant No .863 -2002AA119010)
文摘To classify the frequency modulation signal, this paper employs a parameter invariant filter, which can transfer the frequency modulated information to variety of its envelope, and then extracts the histogram feature to classify the modulation type. This method can efficiently classify the type of a signal such as frequency modulation （FM）, binary frequency shift keyiing （BFSK）, quadrature frequency shift keying （QFSK）, 8-ary frequency shift keying （8FSK）, etc. It can easily be realized and is especially suitable to applications in software radio.
基金Supported by the National Natural Science Foundation for Outstanding Youth(61422102)
文摘A robust finite-horizon Kalman filter is designed for linear discrete-time systems subject to norm-bounded uncertainties in the modeling parameters and missing measurements.The missing measurements were described by a binary switching sequence satisfying a conditional probability distribution,the commonest cases in engineering,such that the expectation of the measurements could be utilized during the iteration process.To consider the uncertainties in the system model,an upperbound for the estimation error covariance was obtained since its real value was unaccessible.Our filter scheme is on the basis of minimizing the obtained upper bound where we refer to the deduction of a classic Kalman filter thus calculation of the derivatives are avoided.Simulations are presented to illustrate the effectiveness of the proposed approach.
基金supported by the National Natural Science Foundation of China (No. 61271343)the Research Fund for the Doctoral Program of Higher Education of China (No. 20122302110012)the 2014 Innovation of Science and Technology Program of China Aerospace Science and Technology Corporation
文摘Estimating cross-range velocity is a challenging task for space-borne synthetic aperture radar（SAR）, which is important for ground moving target indication（GMTI）. Because the velocity of a target is very small compared with that of the satellite, it is difficult to correctly estimate it using a conventional monostatic platform algorithm. To overcome this problem, a novel method employing multistatic SAR is presented in this letter. The proposed hybrid method, which is based on an extended space-time model（ESTIM） of the azimuth signal, has two steps： first, a set of finite impulse response（FIR） filter banks based on a fractional Fourier transform（FrFT） is used to separate multiple targets within a range gate; second, a cross-correlation spectrum weighted subspace fitting（CSWSF） algorithm is applied to each of the separated signals in order to estimate their respective parameters. As verified through computer simulation with the constellations of Cartwheel, Pendulum and Helix, this proposed time-frequency-subspace method effectively improves the estimation precision of the cross-range velocities of multiple targets.
文摘Channel friction is an important parameter in hydraulic analysis. A channel friction parameter inversion method based on Kalman Filter with unknown parameter vector is proposed. Numerical simulations indicate that when the number of monitoring stations exceeds a critical value, the so lution is hardly affected. In addition, Kalman Filter with unknown parameter vector is effective only at unsteady state. For the nonlinear equations, computations of sensitivity matrices are time-costly. Two simplified measures can reduce computing time, but not influence the results. One is to reduce sensitivity matrix analysis time, the other is to substitute for sensitivity matrix.
