In this paper,we proposed a monopulse forward-looking high-resolution imaging algorithm based on adaptive iteration for missile-borne detector.Through iteration,the proposed algorithm automatically selects the echo si...In this paper,we proposed a monopulse forward-looking high-resolution imaging algorithm based on adaptive iteration for missile-borne detector.Through iteration,the proposed algorithm automatically selects the echo signal of isolated strong-scattering points from the receiving echo signal data to accurately estimate the actual optimal monopulse response curve(MRC) of the same distance range,and we applied optimal MRC to realize the azimuth self-focusing in the process of imaging.We use real-time echo data to perform error correction for obtaining the optimal MRC,and the azimuth angulation accuracy may reach the optimum at a certain distance dimension.We experimentally demonstrate the validity,reliability and high performance of the proposed algorithm.The azimuth angulation accuracy may reach up to ten times of the detection beam-width.The simulation experiments have verified the feasibility of this strategy,with the average height measurement error being 7.8%.In the out-field unmanned aerial vehicle(UAV) tests,the height measurement error is less than 25 m,and the whole response time can satisfy the requirements of a missile-borne detector.展开更多
In the missile-borne Strapdown Inertial Navigation System/Global Navigation Satellite System(SINS/GNSS)integrated navigation system,due to the factors such as the high dynamics,the signal blocking by obstacles,the sig...In the missile-borne Strapdown Inertial Navigation System/Global Navigation Satellite System(SINS/GNSS)integrated navigation system,due to the factors such as the high dynamics,the signal blocking by obstacles,the signal intefereces,etc.,there always exist pulse interferences or measurement information interruptions in the satellite receiver,which make nonstationary measurement process.The traditional Kalman Filter(KF)can tackle the state estimation problem under Gaussian white noise,but its performance will be significantly reduced under nonGaussian noises.In order to deal with the non-Gaussian conditions in the actual missile-borne SINS/GNSS integrated navigation systems,a Maximum Versoria Criterion Extended Kalman Filter(MVC-EKF)algorithm is proposed based on the MVC and the idea of M-estimation,which assigns a smaller weight to the anomalous measurements so as to suppress the influence of anomalous measurements on the state estimation while maintaining a relatively low calculation cost.Finally,the integrated navigation simulation experiments prove the effectiveness and robustness of the proposed algorithm.展开更多
基金The name of the project that funded this article is 13th Five-Year Plan"equipment pre-research project,the number of this project is 30107030803。
文摘In this paper,we proposed a monopulse forward-looking high-resolution imaging algorithm based on adaptive iteration for missile-borne detector.Through iteration,the proposed algorithm automatically selects the echo signal of isolated strong-scattering points from the receiving echo signal data to accurately estimate the actual optimal monopulse response curve(MRC) of the same distance range,and we applied optimal MRC to realize the azimuth self-focusing in the process of imaging.We use real-time echo data to perform error correction for obtaining the optimal MRC,and the azimuth angulation accuracy may reach the optimum at a certain distance dimension.We experimentally demonstrate the validity,reliability and high performance of the proposed algorithm.The azimuth angulation accuracy may reach up to ten times of the detection beam-width.The simulation experiments have verified the feasibility of this strategy,with the average height measurement error being 7.8%.In the out-field unmanned aerial vehicle(UAV) tests,the height measurement error is less than 25 m,and the whole response time can satisfy the requirements of a missile-borne detector.
基金co-supported by the National Natural Science Foundation of China(No.62073264)the Key Research and Development Project of Shaanxi Province,China(No.2021ZDLGY01-01 and 2020ZDLGY06-02)+2 种基金National Natural Science Foundation of China(No.61803309)China Postdoctoral Science Foundation(No.2018M633574)the Aeronautical Science Foundation of China(No.2019ZA053008)。
文摘In the missile-borne Strapdown Inertial Navigation System/Global Navigation Satellite System(SINS/GNSS)integrated navigation system,due to the factors such as the high dynamics,the signal blocking by obstacles,the signal intefereces,etc.,there always exist pulse interferences or measurement information interruptions in the satellite receiver,which make nonstationary measurement process.The traditional Kalman Filter(KF)can tackle the state estimation problem under Gaussian white noise,but its performance will be significantly reduced under nonGaussian noises.In order to deal with the non-Gaussian conditions in the actual missile-borne SINS/GNSS integrated navigation systems,a Maximum Versoria Criterion Extended Kalman Filter(MVC-EKF)algorithm is proposed based on the MVC and the idea of M-estimation,which assigns a smaller weight to the anomalous measurements so as to suppress the influence of anomalous measurements on the state estimation while maintaining a relatively low calculation cost.Finally,the integrated navigation simulation experiments prove the effectiveness and robustness of the proposed algorithm.