天波超视距雷达(over the horizonradar,OTHR)通过快速傅里叶变换(fastFouriertransform,FFT)实现长时间相干积累,但这种基于目标速度恒定的方法对于机动目标的效果并不好。提出了一种基于目标运动参数估计的OTHR机动目标检测方法。该...天波超视距雷达(over the horizonradar,OTHR)通过快速傅里叶变换(fastFouriertransform,FFT)实现长时间相干积累,但这种基于目标速度恒定的方法对于机动目标的效果并不好。提出了一种基于目标运动参数估计的OTHR机动目标检测方法。该方法首先确定机动目标的运动参数的大致范围,然后对其运动参数进行估计,之后对其径向加速度进行补偿,最后对经加速度补偿后的目标信号进行相干积累并在距离 多普勒平面上进行二维恒虚警检测。仿真结果表明,该方法能够增强OTHR对机动目标的检测能力,运算效率高,实用性强。展开更多
Continuous and stable tracking of the ground maneuvering target is a challenging problem due to the complex terrain and high clutter. A collaborative tracking method of the multisensor network is presented for the gro...Continuous and stable tracking of the ground maneuvering target is a challenging problem due to the complex terrain and high clutter. A collaborative tracking method of the multisensor network is presented for the ground maneuvering target in the presence of the detection blind zone(DBZ). First, the sensor scheduling process is modeled within the partially observable Markov decision process(POMDP) framework. To evaluate the target tracking accuracy of the sensor, the Fisher information is applied to constructing the reward function. The key of the proposed scheduling method is forecasting and early decisionmaking. Thus, an approximate method based on unscented sampling is presented to estimate the target state and the multi-step scheduling reward over the prediction time horizon. Moreover, the problem is converted into a nonlinear optimization problem, and a fast search algorithm is given to solve the sensor scheduling scheme quickly. Simulation results demonstrate the proposed nonmyopic scheduling method(Non-MSM) has a better target tracking accuracy compared with traditional methods.展开更多
Long-time coherent integration(LTCI)is an effective way for radar maneuvering target detection,but it faces the problem of a large number of search parameters and large amount of calculation.Realizing the simultaneous...Long-time coherent integration(LTCI)is an effective way for radar maneuvering target detection,but it faces the problem of a large number of search parameters and large amount of calculation.Realizing the simultaneous compensation of the range and Doppler migrations in complex clutter back-ground,and at the same time improving the calculation efficiency has become an urgent problem to be solved.The sparse transformation theory is introduced to LTCI in this paper,and a non-parametric searching sparse LTCI(SLTCI)based maneuvering target detection method is proposed.This method performs time reversal(TR)and second-order Keystone transform(SKT)in the range frequency&slow-time data to complete high-order range walk compensation,and achieves the coherent integra-tion of maneuvering target across range and Doppler units via the robust sparse fractional Fourier transform(RSFRFT).It can compensate for the nonlinear range migration caused by high-order motion.S-band and X-band radar data measured in sea clutter background are used to verify the detection performance of the proposed method,which can achieve better detection performance of maneuvering targets with less computational burden compared with several popular integration methods.展开更多
文摘天波超视距雷达(over the horizonradar,OTHR)通过快速傅里叶变换(fastFouriertransform,FFT)实现长时间相干积累,但这种基于目标速度恒定的方法对于机动目标的效果并不好。提出了一种基于目标运动参数估计的OTHR机动目标检测方法。该方法首先确定机动目标的运动参数的大致范围,然后对其运动参数进行估计,之后对其径向加速度进行补偿,最后对经加速度补偿后的目标信号进行相干积累并在距离 多普勒平面上进行二维恒虚警检测。仿真结果表明,该方法能够增强OTHR对机动目标的检测能力,运算效率高,实用性强。
基金supported by the National Defense Pre-Research Foundation of China(0102015012600A2203)。
文摘Continuous and stable tracking of the ground maneuvering target is a challenging problem due to the complex terrain and high clutter. A collaborative tracking method of the multisensor network is presented for the ground maneuvering target in the presence of the detection blind zone(DBZ). First, the sensor scheduling process is modeled within the partially observable Markov decision process(POMDP) framework. To evaluate the target tracking accuracy of the sensor, the Fisher information is applied to constructing the reward function. The key of the proposed scheduling method is forecasting and early decisionmaking. Thus, an approximate method based on unscented sampling is presented to estimate the target state and the multi-step scheduling reward over the prediction time horizon. Moreover, the problem is converted into a nonlinear optimization problem, and a fast search algorithm is given to solve the sensor scheduling scheme quickly. Simulation results demonstrate the proposed nonmyopic scheduling method(Non-MSM) has a better target tracking accuracy compared with traditional methods.
基金supported by the National Natural Science Foundation of China(62222120,61871391,U1933135)Shandong Provincial Natural Science Foundation(ZR2021YQ43).
文摘Long-time coherent integration(LTCI)is an effective way for radar maneuvering target detection,but it faces the problem of a large number of search parameters and large amount of calculation.Realizing the simultaneous compensation of the range and Doppler migrations in complex clutter back-ground,and at the same time improving the calculation efficiency has become an urgent problem to be solved.The sparse transformation theory is introduced to LTCI in this paper,and a non-parametric searching sparse LTCI(SLTCI)based maneuvering target detection method is proposed.This method performs time reversal(TR)and second-order Keystone transform(SKT)in the range frequency&slow-time data to complete high-order range walk compensation,and achieves the coherent integra-tion of maneuvering target across range and Doppler units via the robust sparse fractional Fourier transform(RSFRFT).It can compensate for the nonlinear range migration caused by high-order motion.S-band and X-band radar data measured in sea clutter background are used to verify the detection performance of the proposed method,which can achieve better detection performance of maneuvering targets with less computational burden compared with several popular integration methods.
