We present a novel adaptive filtering approach to the dynamic characterization of waves of varying frequencies and amplitudes embedded in arbitrary noise backgrounds. This method, known as IWAVE (Iterative Wave Action angle Variable Estimator), possesses critical advantages over conventional techniques, making it a useful new tool in the dynamic characterization of a wide range of data containing embedded oscillating signals. After a review of existing techniques, we present the IWAVE algorithm, derive its key characteristics, and provide tests of its performance using simulated and real world data.

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We present a novel adaptive filtering approach to the dynamic characterisation of waves of varying frequency and amplitude embedded in arbitrary noise backgrounds. This method, known as IWAVE, possesses critical advantages over conventional techniques making it a useful new tool in the dynamic characterisation of a wide range of data containing embedded oscillating signals. After a review of existing techniques, we present the IWAVE algorithm, derive its key characteristics, and provide tests of its performance using simulated and real world data.