A station identification method, device and equipment

Abstract

The invention relates to an identifying method, a device and an apparatus for a station. The method comprises the following steps: pre-establishing a correspondence between a station and a monitoringstation, and constructing a standard space feature vector library of the station; obtaining a station list in a target frequency band; for each target station: obtaining a monitoring station list according to the correspondence; collecting real-time monitoring information of the target monitoring station on the target station, and establishing a real-time space feature vector of the target station; and perform a matching in the standard space feature vector library according to the real-time space feature vector, and determining the target station as a legal station when the matching is successful; the monitoring station list comprises the target monitoring station corresponding to the target station. The invention can be used for automatic identification of stations, detecting illegal stations, improving the accuracy and effectiveness of supervision to serve the supervision work of radio stations.

Description

technical field [0001] The invention relates to the field of radio station monitoring, in particular to a station identification method, device and equipment. Background technique [0002] The traditional station identification algorithm is realized by identifying the signal transmitted by the station. The signal identification method includes the characteristic parameter method, the artificial intelligence identification method and the method based on the support vector machine, etc. The characteristic parameter method is based on the instantaneous amplitude of the signal. , instantaneous phase, instantaneous frequency characteristic parameters and other differences to identify, this method is simple and has a small amount of calculation, but it is greatly affected by the signal-to-noise ratio; artificial intelligence identification methods mainly use artificial intelligence such as expert systems, artificial neural networks, fuzzy reasoning, and genetic algorithms. The int...

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Problems solved by technology

[0002] The traditional station identification algorithm is realized by identifying the signal transmitted by the station. The signal identification method includes the characteristic parameter method, the artificial intelligence identification method and the method based on the support vector machine, etc. The characteristic parameter method is based on the instantaneous amplitude of the signal. , instantaneous phase, instantaneous frequency characteristic parameters and other differences to identify, this method is simple and has a small amount of calculation, but it is greatly affected by the signal-to-noise ratio; artificial intelligence identification methods mainly use artificial intelligence such as expert systems, artificial neural networks, fuzzy reasoning, and genetic algorithms. The intelligent method forms the inference rules of experience and knowledge. This method does not rely on the prior knowledge of the database. It is flexible in analysis and can learn by itself, but it is easy to miss detection and misjudgment; signal recognition based on support vector machine is established by optimizing algorithm functions and models. And parameter selection for signal recognition, this method is good at solving high-dimensional classification problems, the recognition accuracy is relatively high, but the complexity is high, and the theoretical algorithm is not perfect enough

In addition, station identification through signal identification has two serious defects. 1) It is impossible to distinguish stations that transmit the same or similar signals, such as FM radio stations, etc., 2) It relies on the data of a single monitoring station, without considering the station The spatial distribution characteristics of the transmitted signal strength make the identification results have a greater dependence on the environment of the current monitoring station, resulting in a low station identification rate

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