Study on emitter signal recognition based on backward cloud model and attribute similarity
Pan Li-na · 2012
To deal with the problem of radar emitter recognition caused by noise environment, this paper presents a new method for emitter recognition based on backward cloud model and attribute similarity. First, it constructs a radar emitter database included with noise data according with the reality, then calculates the cloud numerical characteristic based on backward cloud model, presents a method of determining recognition weight of coefficients, and a new classification implement based on backward cloud model and attribute similarity is proposed. Simulation results show that the method proposed by this article can deal with the randomicity and vagueness caused by noise environment much better and can conduct emitter recognition effectively in the adverse noise envioroment.