9 results about "Space-based radar" patented technology

The application discloses a kind of distributed space-based radar networking tracking methods based on message passing, based on the distributed space-based radar networking of multiple satellite platforms, antenna array, transmitting system, receiving system, radar power etc., the method comprises: the sequence of first target motion state, target visible state, data association and latent variable in joint observation variable are described using factor graph;Based on the connection relationship of variable node and factor node in factor graph, the approximate solution of joint posterior probability density is solved using BP-MF combined approximation method;According to the approximate solution of joint probability density, the target is tracked.The present application is based on the distributed space-based radar networking, combines factor graph and uses BP-MF combined approximation method to convert the solution of high-dimensional posterior probability density fitting into the solution of low-dimensional posterior probability density product, solves the problem of cumulative propagation of estimation error and identification risk in the case of guaranteeing networking performance using distributed networking tracking method, avoids.

This invention discloses a method for short-range measurement and tracking of large space targets by space-based radar. Addressing the angular scintillation effect caused by the large local RCS of large and complex space targets during short-range measurement and tracking, the method extracts target body shape feature information by constructing a target measurement time window, performs data correlation filtering on multiple measurements to eliminate interference from the target's local RCS impact response points, and provides an offset tracking scheme for situations with large local RCS interference, ensuring the radar beam always points towards the target body, effectively improving the accuracy and stability of radar tracking of the target body under local RCS interference.

The application provides a kind of relative attitude autonomous measurement method between multiple space vehicles based on space-based radar precision measurement.Space formation space vehicles are all equipped with space-based radar, and can measure relative distance and angle, which is converted into LOS observation vector in each space vehicle body coordinate system;Since the same physical line-of-sight vector in different space vehicle body coordinate systems satisfies the rotation matrix transformation relationship, multiple non-collinear LOS vectors are obtained through mutual observation between multiple space vehicles, and a least squares optimization problem is constructed;The optimal rotation matrix is solved by singular value decomposition, and the result is constrained to SO (3) group to ensure the legality of the rotation matrix, and the complete three-axis relative attitude between space vehicles is finally solved.The application does not need to know the relative attitude and position of the space vehicle as priori, and can realize the relative attitude measurement between any two space vehicles through distance and angle measurement values.

A space-based radar air target nonlinear robust tracking method, the main steps include: constructing a space-based radar target observation geometry model, establishing the conversion relationship between the target state and the measurement; VB approximation method is introduced into the PHD recursive framework, the Gaussian closed solution of PHD filter under unknown measurement noise covariance is derived to solve the problem of measurement noise uncertainty under space-based observation conditions; On this basis, the cubature Kalman filter is introduced into the VB-PHD filter based on Gaussian mixture model, and the third-order spherical radial cubature rule is used to complete the PHD recursive density function integration operation under the nonlinear system model, and the tracking accuracy under strong nonlinear observation conditions is improved. The method can effectively improve the filtering accuracy and improve the robustness of space-based radar air target tracking.

The invention discloses a space-based radar clutter suppression method based on multi-domain cascade processing. The method comprises the following steps: designing a linear frequency modulation signal and a phase coding signal; designing a first waveform signal based on pulse width frequency modulation polarity agility and linear frequency modulation by changing the frequency modulation polarity of the linear frequency modulation signal, and designing a second waveform signal based on phase coding, pulse width frequency modulation polarity agility and linear frequency modulation according to the phase coding signal and the first waveform signal; based on a minimum peak sidelobe energy criterion, designing an orthogonal waveform signal group about the second waveform signal by adopting an SQP algorithm; clutter space-time snapshot data are calculated according to the orthogonal waveform signal group; designing a matched filter according to the orthogonal waveform signal group and filtering clutter space-time snapshot data; calculating a weight coefficient of a space-time two-dimensional filter according to the filtered clutter space-time snapshot data by adopting a 3DT-STAP algorithm; and calculating a clutter suppression result according to the filtered clutter space-time snapshot data and the weight coefficient of the space-time two-dimensional filter.

The invention provides a space-based and air-based radar cooperative detection method, device and equipment for a sea-skimming stealth target and a storage medium. Relates to the technical field of radar detection simulation. The method comprises the following steps: acquiring a space-based radar frequency, an azimuth angle and a pitch angle, and determining a sea-skimming target and marine environment simulation parameters; calculating a target double-station RCS and an ocean double-station scattering coefficient; according to the target double-station RCS and the ocean double-station scattering coefficient, the echo signal-to-clutter ratio in a single radar resolution unit of each azimuth angle is calculated; based on the distribution rule of the echo signal-to-clutter ratio along with the receiving azimuth angle, taking the azimuth angle corresponding to the minimum value of the signal-to-clutter ratio as the azimuth of the receiver; and changing the pitch angle at least once, recalculating the echo signal-to-clutter ratio until the azimuth angle of the receiver is located in the forward scattering target area, and taking the currently determined azimuth angle of the receiver as the final deployment azimuth of the airborne receiving radar. According to the invention, long-distance detection of the ultra-low penetration defense stealth target can be realized.

The invention provides a method and a system for constructing a space-based radar transcendental linear processing framework. The method comprises the following steps: carrying out backward signal-level closed-loop processing by using single-frame data; target track information obtained through forward inter-stage iteration information-stage processing is used for returning to signal-stage processing of a current frame, and clutter suppression and target detection processing are assisted; using the target position and speed information obtained by the information level processing for the signal level processing of subsequent frames by using backward inter-level iterative processing; feeding back target information to a previous processing link through a forward scanning closed loop, performing signal-level and information-level processing again, checking whether the target can be detected and tracked, and updating a target library; and through a backward scanning closed loop, detected target information is fed back to next scanning, prior information used in links of clutter suppression, detection and the like is optimized, and signal-level and information-level processing is performed again. According to the method, the harsh constraint of space-based radar weak and small target detection on physical implementation is effectively reduced.

This paper utilizes ground-based and space-based radars to construct a novel Bi-ISAR architecture with significant advantages, including wide coverage and high flexibility. Furthermore, a sparse-aperture Bi-ISAR imaging and calibration method based on the FAIWF-CICPF-CTF algorithm is proposed for this Bi-ISAR system. This imaging and calibration method breaks with traditional thinking by innovatively transforming the sparse-aperture Bi-ISAR imaging and calibration problem into a sparse signal recovery problem in the CFCR domain, providing a new paradigm for sparse-aperture Bi-ISAR imaging and calibration. Benefiting from the excellent energy accumulation and noise suppression performance of the CICPF algorithm and the superior reconstruction performance of the proposed adaptive iterative Wiener filter, this method demonstrates superior performance compared to existing algorithms under conditions of low signal-to-noise ratios and high data loss rates.

The present invention provides a space-based ISAR autofocusing fast motion compensation method accelerated by GPU parallelization. The method utilizes echo data and angle measurement information of space targets measured by space-based radar, and utilizes GPU parallel processing architecture to synchronously calculate and fit radar angle information. Then, by parallelizing polar coordinate resampling, loop statements are reduced, front-to-back coupling correlation is reduced, and efficient two-dimensional motion decoupling is achieved. Then, a polar coordinate format algorithm and a motion error inversion scheme are combined to perform distance downsampling on the signal after two-dimensional motion decoupling, and valid data segments are intercepted to reduce the data volume. Phase gradient autofocusing and image minimum entropy autofocusing are used in stages to estimate the non-space-varying error of the distance. Then, the GPU parallel processing architecture is used to implement parallel processing of phase gradient autofocusing and image minimum entropy autofocusing, and space-varying error is interpolated and estimated using the estimated error, thereby improving estimation accuracy and computational efficiency, and completing robust focused imaging of space targets.