Machine-swept mine angle super-resolution angle measurement method based on improved maximum likelihood algorithm

Abstract

The invention discloses a machine-swept radar angle super-resolution angle measurement method based on an improved maximum likelihood algorithm. The method comprises the following steps of: analyzingthe characteristics of a machine-swept radar signal, constructing a machine-swept radar signal model, constructing a maximum likelihood function based on the model according to the characteristics ofthe model and the property of a maximum likelihood algorithm, and solving a problem that the number of information sources needs to be known in advance in the maximum likelihood function by assuming aknown mode. Therefore, the method can better meet actual engineering requirements; and meanwhile, the maximum likelihood solution is solved by using intelligent algorithms such as a genetic algorithmor an ant colony algorithm, so that problems of long time and large calculated amount of common space search are solved.

Description

technical field [0001] The invention belongs to the technical field of radar signal processing algorithms, and in particular relates to a machine-scanning radar angle super-resolution angle measurement method based on an improved maximum likelihood algorithm. Background technique [0002] Ordinary machine-scan radars use the rotation of the antenna to change the pointing to achieve scanning. The scanning method is simple and the performance is stable and reliable. A principle of machine-scanning radar detection target performance is: the radar antenna continuously emits radar beams during the scanning process, and the radar waves are reflected back when they meet the target. The reflected echoes will be received by the radar again, and then undergo a series of signal processing. It can solve the target's shape, size, speed, position and other information. However, the above detection of the target is based on the fact that there is only one target at the same distance from ...

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Problems solved by technology

[0004] The traditional maximum likelihood algorithm has two major shortcomings in the application of angle super-resolution: first, the essence of the algorithm is to find the extreme value of a nonlinear function, which is difficult to solve and requires a large amount of calculation; second, it needs to know the source in advance The number of numbers cannot be applied to the actual situation where the number of sources is unknown

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