Abstract
EFA (extended factored approach) algorithm is the main method of space-time adaptive processing technology (STAP) for airborne phased array radar, but it is faced with many problems, such as large number of samples and large amount of calculation. Therefore, this paper uses a method of spatial data dimensionality reduction processing based on cyclic iterative calculation to optimize its STAP. The final experimental results show that, after spatial data dimensionality reduction processing optimization, the STAP performance of EFA algorithm is further expanded in the range of sample number adaptation; especially in the case of small sample number, the optimized STAP performance has been basically close to the ideal compared with other optimization schemes; tap performance also proves that the optimization scheme in this paper has better convergence speed and STAP performance.
Highlights
Airborne radar is the key military technology to win the war, especially the modern early warning aircraft with airborne phased array radar as the main detection means, which is called the air combat force multiplier of modern war, so the research on airborne phased array radar technology has been endless. e biggest advantage of airborne phased array radar is that its platform can bring it into the high altitude and scan the airspace through the radio pulse beam in the high altitude, so its detection range and distance are greatly increased
Because the airborne phased array radar is flying at high altitude, it will receive a lot of clutter when it scans at high altitude. erefore, clutter suppression becomes the main direction to improve the performance of phased array radar
EFA algorithm in space-time adaptive processing technology (STAP) needs a large number of samples and computation, so a method of spatial data dimensionality reduction based on cyclic iterative calculation is adopted to optimize EFA algorithm
Summary
Airborne radar is the key military technology to win the war, especially the modern early warning aircraft with airborne phased array radar as the main detection means, which is called the air combat force multiplier of modern war, so the research on airborne phased array radar technology has been endless. e biggest advantage of airborne phased array radar is that its platform can bring it into the high altitude and scan the airspace through the radio pulse beam in the high altitude, so its detection range and distance are greatly increased. E radio pulse beam fed back to phased array radar antenna array is processed by signal machine to form scanning information, which includes interested target information and clutter information and interference information How to eliminate these clutter and interference information has become the key direction to improve the performance of airborne phased array radar. Erefore, based on the analysis of EFA algorithm and STAP technology, this paper proposes an innovative spatial dimension reduction method to optimize the STAP technology performance, so that it can break through the limitation of sample size, further improve the Mathematical Problems in Engineering ability of STAP to process clutter, and improve the detection ability of airborne phased array radar. Is research includes three parts. e first part is the summary and analysis of STAP technology by domestic and foreign research institutions and scholars. e second part mainly introduces the airborne phased array radar and its clutter model, the related concepts of EFA technology, as well as the detailed airspace dimensionality reduction measures. e third part is to simulate and verify the improved STAP technology of this study and confirm whether the improvement measures of this study can effectively improve the performance of STAP
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