This dissertation focuses on advanced signal processing techniques for multicarrier modulation in two application scenarios: underwater acoustic (UWA) communication and passive radar.;In UWA communication, multicarrier transmission promises a substantial increase in data rate, following the path of recent success of broadband wireless radio communications. However. UWA channels are much more challenging than their radio counterparts, due to strong multipath and significant Doppler effects. Advanced signal processing dedicated to the UWA environment is indispensable to realize successful multicarrier modulation in underwater environments. In this talk, I will present a receiver design where the channel estimator exploits the sparsity nature of the UWA channel and the demodulator can effectively suppress the inter-carrier interference (ICI). The channel estimators include subspace algorithms from the array processing literature, namely root-MUSIC and ESPRIT, and recent compressed sensing algorithms in form of Orthogonal Matching Pursuit (OMP) and Basis Pursuit (BP). Results from a recent experiment organized by the Office of Naval Research (ONR) will be presented for performance demonstration.;In passive radar, multicarrier waveforms in the form of Digital Audio Broadcast (DAB) are used as illuminators of opportunity to detect and locate airborne targets. As signal reflections off the targets compose additional time-varying multipath components, target detection and localization are feasible through advanced channel estimation algorithms that, can detect path variation. In this scenario, super-resolution subspace methods like MUSIC, or BP from the field of compressed sensing are proposed. These advanced methods can improve clutter suppression and target resolution in the passive radar application.
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