In a global positioning system(GPS)passive radar,a high resolution requires a high sampling frequency,which increases the computational load.Balancing the computational load and the range resolution is challenging.Thi...In a global positioning system(GPS)passive radar,a high resolution requires a high sampling frequency,which increases the computational load.Balancing the computational load and the range resolution is challenging.This paper presents a method to trade off the range resolution and the computational load by experimentally determining the optimal sampling frequency through an analysis of multiple sets of GPS satellite data at different sampling frequencies.The test data are used to construct a range resolution-sampling frequency trade-off model using least-squares estimation.The theoretical analysis shows that the experimental data are the best fit using smoothing and nthorder derivative splines.Using field GPS C/A code signal-based GPS radar,the trade-off between the optimal sampling frequency is determined to be in the 20461.25–24553.5 kHz range,which supports a resolution of 43–48 m.Compared with the conventional method,the CPU time is reduced by approximately 50%.展开更多
In this paper, the problem of parameter estimation of the combined radar signal adopting chaotic pulse position modulation （CPPM） and linear frequency modulation （LFM）, which can be widely used in electronic count...In this paper, the problem of parameter estimation of the combined radar signal adopting chaotic pulse position modulation （CPPM） and linear frequency modulation （LFM）, which can be widely used in electronic countermeasures, is addressed. An approach is proposed to estimate the initial frequency and chirp rate of the combined signal by exploiting the second-order cyclostationarity of the intra-pulse signal. In addition, under the condition of the equal pulse width, the pulse repetition interval （PRI） of the combined signal is predicted using the low-order Volterra adaptive filter. Simulations demonstrate that the proposed cyclic autocorrelation Hough transform （CHT） algorithm is theoretically tolerant to additive white Gaussian noise. When the value of signal noise to ratio （SNR） is less than 4 dB, it can still estimate the intra-pulse parameters well. When SNR = 3 dB, a good prediction of the PRI sequence can be achieved by the Volterra adaptive filter algorithm, even only 100 training samples.展开更多
基金supported by the National Natural Science Foundation of China(42001297)the Research Foundation of Education Department of Hunan Province(19B061)the National Natural Science Foundation of Hunan Province(2021JJ40631)。
文摘In a global positioning system(GPS)passive radar,a high resolution requires a high sampling frequency,which increases the computational load.Balancing the computational load and the range resolution is challenging.This paper presents a method to trade off the range resolution and the computational load by experimentally determining the optimal sampling frequency through an analysis of multiple sets of GPS satellite data at different sampling frequencies.The test data are used to construct a range resolution-sampling frequency trade-off model using least-squares estimation.The theoretical analysis shows that the experimental data are the best fit using smoothing and nthorder derivative splines.Using field GPS C/A code signal-based GPS radar,the trade-off between the optimal sampling frequency is determined to be in the 20461.25–24553.5 kHz range,which supports a resolution of 43–48 m.Compared with the conventional method,the CPU time is reduced by approximately 50%.
基金supported by the National Natural Science Foundation of China under Grant 61172116
文摘In this paper, the problem of parameter estimation of the combined radar signal adopting chaotic pulse position modulation （CPPM） and linear frequency modulation （LFM）, which can be widely used in electronic countermeasures, is addressed. An approach is proposed to estimate the initial frequency and chirp rate of the combined signal by exploiting the second-order cyclostationarity of the intra-pulse signal. In addition, under the condition of the equal pulse width, the pulse repetition interval （PRI） of the combined signal is predicted using the low-order Volterra adaptive filter. Simulations demonstrate that the proposed cyclic autocorrelation Hough transform （CHT） algorithm is theoretically tolerant to additive white Gaussian noise. When the value of signal noise to ratio （SNR） is less than 4 dB, it can still estimate the intra-pulse parameters well. When SNR = 3 dB, a good prediction of the PRI sequence can be achieved by the Volterra adaptive filter algorithm, even only 100 training samples.
