Small Boat Detection via Time-Frequency Analysis and DenseNet

Small boat detection under the influence of sea clutter is usually difficult, especially for the low-resolution pulse Doppler Radar, as the amplitude of the boat is covered by sea clutter in the time domain, and the spectrum of the boat and sea clutter overlap in the frequency domain. DenseNet can establish a dense connection between all the front layers and the back layer to achieve state-of-the-art results on various tasks. This paper proposes a new method for the detection task based on time-frequency analysis and DenseNet. This method can automatically extract the characteristics of sea clutter and boat in time-frequency images and complete the classification task. The accuracy of the classification is 98.75 percent, which has an improvement of 18.25 percent than the accuracy of LeNet-5. The measured data verified the method.