Airborne radar clutter suppression method based on launching space-time weight optimization and KA-STAP

Abstract

The invention belonging to the field of airborne array radar clutter suppression provides an airborne radar clutter suppression method based on launching space-time weight optimization and KA-STAP. On the basis of the traditional KA-STAP, the available freedom degree of a radar transmitting terminal is utilized fully; according to an array structure and clutter prior information, a launching space-time weight vector is designed to suppress mainlobe and sidelobe clutters so as to reducing the received clutter peak energy and keep the complete clutter information estimation prior covariance matrix; and then an estimated covariance matrix is loaded based on the constructed prior covariance matrix and calculation is carried out to obtain a received STAP filter space-time optimal weight. Compared with the conventional launching plus KA-STAP method, the provided method has the following beneficial effect: the launching freedom degree is introduced to reducing the clutter peak energy in echo and reducing the dynamic range of the received signal; and compared with the launching space-time weight optimization method, the provided method has the following advantage: the certain clutter information is kept in the echo and thus the clutter can be suppressed at the receiving terminal by the KA-STAP.

Description

technical field [0001] The invention belongs to the field of airborne array radar clutter suppression, in particular to an airborne radar clutter suppression method based on emission space-time weight optimization and knowledge-assisted space-time adaptive processing (KA-STAP). Background technique [0002] Space-Time Adaptive Processing (STAP) is an important technology applied to airborne array radar. STAP uses training samples to estimate the covariance matrix of the Cell Under Test (CUT) and designs a receiving filter to suppress Clutter, improve the signal-to-clutter-plus-noise ratio (Signal-to-clutter-plus-noise Ratio, SCNR). The RMB criterion points out that the number of independent and identically distributed (I ID) training samples required for covariance matrix estimation is at least twice the matrix dimension in order to make the output signal-to-noise ratio loss less than 3dB; but in actual work, The environment faced by airborne radar is usually non-uniform, a...

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Problems solved by technology

Under the same conditions, the transmit space-time weight vector optimization method and the STAP receive SNR can achieve the same effect, but the transmit space-time weight vector design completely depends on the clutter prior information, and the inaccuracy of the prior information will lead to poor performance of the algorithm. significantly decreased (Chen Yangyi, Li Jun, Zhang Shengyu, et al. Space-time joint design of launch weight vectors based on cognition[J]. Radar Science and Technology, 2015(6):650-654.); and, launch space-time weighted It will lead to changes in the spectral characteristics of the received clutter and the loss of corresponding clutter information, making it more difficult to estimate the prior covariance matrix of the received clutter

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