A robust hierarchical digital modulation classification technique: Using linear approximations

Automatic Modulation Recognition has become an essential tool for COMINT. In this paper we use a feature-based method introducing new intuitive features for Real-Time Classification of Digitally modulated signals without any prior knowledge of signal parameters. The incoming signal's basic modulation type is detected i.e. FSK, PSK, ASK QAM & GMSK and then its order is identified. This hierarchical classification can be considered a step towards a general modulation classifier in A WGN channel. Linear Approximations are introduced in Instantaneous Amplitude and Non-Linear Component of Instantaneous Phase which result in improved performance of the system at lower SNR values. Simulations show that with the new feature set classification success rate is 99.9% at very low SNR i.e. 5dB.