Book Description

The underwater channel poses numerous challenges for acoustic communication. Acoustic waves suffer long propagation delay, multipath, fading, and potentially high spatial and temporal variability. In addition, there is no typical underwater acoustic channel; every body of water exhibits quantiably different properties. Underwater acoustic modems are traditionally operated at low frequencies. However, the use of broadband, high frequency communication is a good alternative because of the lower background noise compared to low-frequencies, considerably larger bandwidth and better source transducer efficiency. One of the biggest problems in the underwater acoustic communications at high frequencies is time-selective fading, resulting in the Doppler spread. While many Doppler detection, estimation and compensation techniques can be found in literature, the applications are limited to systems operating at low frequencies contained within frequencies ranging from a few hundred Hertz to around 30 kHz. This dissertation proposes two robust channel estimation techniques for simultaneous transmissions using multiple sources and multiple receivers (MIMO) that closely follows the rapidly time-varying nature of the underwater channel. The first method is a trended least square (LS) estimation that combines the traditional LS method with an empirical modal decomposition (EMD) based trend extraction algorithm. This method allows separating the slow fading modes in the MIMO channels from the fast-fading ones and thus achieves a close tracking of the channel impulse response time fluctuations. This dissertation also outlines a time-varying underwater channel estimation method based on the channel sparsity characteristic. The sparsity of the underwater communication channel is exploited by using the MIMO P-iterative greedy orthogonal matching pursuit (MIMO-OMP) algorithm for the channel estimation. Both techniques are demonstrated in a fully controlled environment, using simulated and experimental data. To test the proposed channel estimation techniques, an acoustic model for a MIMO channel is developed using the method of images applied to a completely closed three-dimensional duct with a pressure release surface boundary and five rigid walls. The MIMO simulated channel provides the strength and delay of all echoes forming the channel. Both simulation and experimental results show a signicant improvement in the estimation of the channel impulse response, thus validating the two proposed algorithms.