Abstract
Maximum a posteriori (MAP) techniques are applied to the problem of estimating the unknown parameters of a frequency modulated narrow-band signal in additive white Gaussian noise. Signals are assumed to have unknown amplitude, initial phase, and frequency versus time history, although a priori information concerning the frequency trajectory may be available. In addition, it is assumed that the signal frequency trajectory can be adequately modeled by a continuous piecewise linear function of time. It is shown that the MAP estimator maximizes a linear combination of (1) coherent match of signal induced outputs to received observations, and (2) a term dependent only upon a priori knowledge. This second term reduces to a measure of trajectory smoothness in the special case of a Gauss–Markov a priori frequency model. Lastly, a MAP detection scheme is suggested for cases in which the presence of such signals is an issue.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
