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Understanding of channel propagation characteristics is a key to the optimal design of underwater acoustic communication. Generally, modelling of underwater acoustic channel is performed based on measurement result in certain site at certain times. Different sites might have different characteristics, each of which can generally be described by a model obtained by averaging measurement results at multiple points in the same environment. This paper describes a characterization of the underwater acoustic channel of tropical shallow water in a Mangrove estuary, which has sediment up to 60 cm at the bottom. Such a channel model is beneficial for the design of communication system in an autonomous underwater vehicle, for instance. The measurement result of delay spread parameter from three different points with the distance of 14 ~ 52 m, has various values. The root mean square (RMS) of delay spread ranges between 0.0621 ~ 0.264 ms, and the maximum delay spread varies with the value of 0.187 ~ 1.0 ms. The pdf fitting shows that Rayleigh distribution describes the fading variation more accurately than Nakagami and Ricean.

Understanding the characteristics of channel propagation plays an important role in designing communication systems. Underwater acoustic channel modeling is commonly done by the direct measurement result from a specific location and time. This paper presents an evaluation of channel impulse response (CIR) and power delay profile (PDP) measurements in shallow water environment using three types of probe signals, i.e., pseudonoise (PN)-sequence, exponentially sine swept (ESS), and amplitude-modulated ESS (AM-ESS). The measurements have been carried out in a laboratory-scale towing tank. The ESS signal has been found to produce CIR and PDP that are close to those of the ray tracing model. The multipath pattern of CIR obtained from ESS signal shows an 80% similarity; it was closer to the ray tracing model compared with other results, made using PN-sequence and AM-ESS signals. The estimated value of rms delay spread obtained by the ray tracing model is 1.023 ms and that obtained by the ESS signal is 1.502 ms. Meanwhile, the values obtained by the PN-sequence and AM-ESS signals are 0.769 and 1.410 ms, respectively. In the frequency domain, the spaced-frequency correlation function, obtained using the PN-sequence and ESS signals, is more similar to the ray tracing model compared with the AM-ESS signal.

Understanding of environmental characteristic is a key factor in design of communication system. This paper describes an ambient noise characterization of measurement in the shallow water of Surabaya bay. The result showed that probability density function (pdf) of ambient noise is close to a Gaussian distribution with the mean of −2.85×10−5 V, and deviation standard of 9.87×10−4V. Validation has been done by using mean square error (MSE) and Bhattacharya distance. In the frequency domain analysis, it is showed that in the range of 0 ∲ 9 kHz has a deceasing level from −100 until −140 dB. In the frequency of 9 ∲ 13.5 kHz, the spectral is flat as like a white. It can be used as a reference in decision of range frequency of underwater acoustic communication systems that will be applied.

Development of an underwater acoustic communication system is a necessity for the majority of the nation as a sea area of Indonesia. Most area s of the ocean in Indonesia is shallow, the environment has unique characteristics compared to other countries. It is a challenge in the research underwater acoustic communication system. This paper presented a preliminary study of the developing of soft acoustic modem testbed for underwater acoustic communication system with OFDM technique. Modem has been implemented on a PC with Matlab, with the objective to evaluate the algorithm development. Image file in JPEG format is encoded with a discrete cosine transform (DCT). To improve performance, information is encoded with a forward error correction, FEC-Hamming. The system uses BPSK modulation, OFDM transmission techniques, and using acoustic signal as carrier wave. In this system, the occupation bandwidth is 5.3 kHz, transmission rate of 3.7 k sps, and center frequency at 13.3 kHz. As an initial stage, the model presented in the form of simulator tesbed passband, and is treated with the propagation parameters that was obtained from measurements in a Towing Tank in previous experiment. The next stage is tesbed evaluation through experimental in a laboratory, such the effect of conversion process from electrical to audio signal at PC sound card and the capability of the receiver to recover the information.

Propeller cavitation noise analysis is necessary since this noise is one of the components of the ship noise signature that would be different for each type of the ship. Therefore, the noise can be used for detection and identification process of a ship. This noise can be simulated by doing the experiment generating one component of the ship noise signature, i.e. the propeller cavitation noise. The experiment is done in the cavitation tunnel of the Indonesian Hydrodynamic Laboratory (IHL), Surabaya, Indonesia to generate this noise. Two techniques, i.e. the Wigner-Ville distribution and the backpropagation neural network, are applied to analyse this noise. The results are compared to examine which technique shows better representation.

Acoustic cavitation noise caused by propeller is used in many underwater applications as one of the ships noise signatures. This paper reports characterization process done by measuring the cavitation noise generated by a propeller in a cavitation tunnel. The cavitation tunnel used for the measurement is of the K16B type belonging to the Indonesian Hydrodynamic Laboratory, Surabaya, Indonesia. The experiment is done using a B-series four-blade bronze propeller (diameter 23cm) using a hydrophone placed in the tunnel at window section (60x90)cm2 of the measurement section (400x85x85)cm3. Some of the solutions to get accurate and reliable measurement results include calibration measurement and minimizing acoustic noise system and environment. Preliminary process has been done to analyse the characteristics of the measurement results in the time-frequency domain, with the objective being to detect when and which type of cavitation noise occurs in any kind of condition. Measurement outcomes in the form of acou...