# Performance of Time Reversal Based Underwater Target Detection in Shallow Water
## 1 Introduction  
Detection of objects bottoming at the sea floor in shallow water is a very important problem. It is also essential in underwater exploration for protecting the underwater environment, and is a critical technology in the field of military detection. A side scan sonar is mainly applied in conventional methods to obtain images within detection fields, and studies have been performed to recognize cylindrical targets by using image signal processing [1; 2; 3; 4; 5]. The sonar images used in this process are composed of the intensities of sound waves scattered on the seabed surface or on the target. The resolution of these images is very low, and owing to severe noise it is impossible to detect objects during real-time processing. In addition, since frequencies higher than 100 kHz are used, the detection distance is very short, and the sonar sensors must be towed at very low speed to obtain clean images in which the detection field is relatively narrow. Meanwhile, mid-frequencies are currently used to detect sea mines at the bottom of the seabed in shallow seas. The Applied Physics Lab (APL) at the University of Washington in the United States of America conducted research on the scattering of sound waves from a 1\(\sim\)2 m-long target [6; 7]. In the study, frequencies of 1\(\sim\)30 kHz are used to conduct comparative research between actual test data and simulation data on the scattering of sound waves in various cylindrical objects. Research is performed on the signal intensity reflected from the target rather than the images of the target, and characteristics on the seabed in contact with the target are modeled. In shallow water environments with fast current such as the Yellow Sea in Korea, the detection problem is more difficult. Note that the average speed of 74.0 cm/s with the maximum speed of 172.6 cm/s has been observed near the Taean Peninsula in the Yellow Sea [8], and its sediment consists of 85% gravel and 15% sand on average [9]. This is a very complicated area that includescoastal fronts and swirls, substantial tides and currents, abundant sea life, and high ship traffic. These factors are changing temporally and/or spatially, and combine to create a difficult detection problem [10; 11]. When detecting a target via active sonar, the received signal includes not only the target response but also the clutter response due to surrounding objects. Furthermore, the effect of clutter becomes stronger in the shallow water environment. It is not easy to model the channels of the clutters because of their time-varying characteristics. Studies on channel modeling in shallow water have been actively conducted [12]. Clutter is the factor that interferes with the detection of targets [13]. Intensive studies on reducing the influence of clutter or identifying objects and clutter have been done in various ways [14]. In the sonar system, as the complexity of the channel structure increases, detection performance deteriorates exponentially. Since [PERSON] and his group proposed the time reversal techniques in acoustics [15; 16; 17], research has been carried out in a variety of fields, from electromagnetism to underwater acoustics. Significant theoretical and experimental efforts have been made to improve the detection and imaging algorithms in a considerable scattering environment [18; 19; 20; 21]. The time reversal technique requires that targets are in uniform background media [22] in order to obtain clean images. In terms of detection, the target signal is usually covered or disturbed by the clutter signal. By capturing the received wave which radiated from the source and retransmitting the time-reversed waveform of the captured signal to the channel for reception, the energy of the wave can be focused at a specific position [23; 24]. Note that retransmitting the time reversal signal from the received signal is a kind of matched filtering for the time-invariant components, while it is a kind of energy spreading for the time-varying components [25].