Space luminous environment adaptability of missile-borne star sensor

To solve the problem of stray interference to star point target identification while a star sensor imaging to the sky, a study on space luminous environment adaptability of missile-borne star sensor was carried out. By Plank blackbody radiation law and some astronomic knowledge, irradiancies of the stray at the star sensor working height were estimated. By relative astrophysical and mathematics knowledge, included angles between the star sensor optical axis point and the stray at any moment were calculated. The calculation correctness was verified with the star map software of Stellarium. By combining the upper analysis with the baffle suppression effect, a real-time model for space luminous environment of missile-borne star sensor was proposed. By signal-noise rate （SNR） criterion, the adaptability of missile-borne star sensor to space luminous environment was studied. As an example, a certain type of star sensor was considered when imaging to the starry sky on June 22, 2011 （the Summer Solstice） and September 20, 2011 （August 23 of the lunar year, last quarter moon） in Beijing. The space luminous environment and the adaptability to it were simulated and analyzed at the star sensor working height. In each period of time, the stray suppression of the baffle is analyzed by comparing the calculated included angle between the star sensor optical axis point and the stray with the shielded provided by system index. When the included angle is larger than the shielded angle and less than 90~, the stray is restrained by the baffle. The stray effect on star point target identification is analyzed by comparing the irradiancy of 6 magnitude star with that of the stray on star sensor sensitization surface. When the irradiancy of 6 magnitude star is 5 times more than that of the stray, there is no effect on the star point target identification. The simulation results are identicat with the actual situation. The space luminous environment of the missile-borne star sensor can be estimated real-timely by this model. The adaptability of the star sensor to space luminous environment can be analyzed conveniently. A basis for determining the relative star sensor indexes, the navigation star chosen strategy and the missile launch window can be provided.

Research on monopulse forward-looking high-resolution imaging algorithm based on adaptive iteration

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.

SINS/GNSS integrated navigation system based on maximum versoria filter

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.