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Imaging for Detection and Identification
A noise canceling technique based on a model-based recursive processor is presented. Beginning with a canceling scheme using a reference source, it is shown how to obtain an estimate of the noise, which can then be incorporated in a recursive noise canceler. Once this is done, recursive detection and estimation schemes are developed. The approach is to model the nonstationary noise as an autoregressive process, which can then easily be placed into a state-space canonical form. This results in adoi:10.1007/978-1-4020-5620-8_5 fatcat:3ikc42hudnhdfkh7jxsogmygxu