Low-observable target detection in sea clutter based on the adaptive 3D-IFS algorithm

This paper mainly studies the application of the fractal self-affine theory for weak target detection in sea clutter. In this paper, the adaptive 3D-IFS (3D-IFS: three-dimensional iterated function system) algorithm is presented and a novel weak target detection model is proposed based on the algorithm. To accurately extract the weak target from the complicated background of sea clutter, we use the radar echo model of the LFM radar and the target detection model to calculate the prediction error of radar echoes. Furthermore, based on extensive analysis and simulation, we identify the scale factor, polarization model and target state as three key factors that affect the detection performance of our proposed model. Using the real data from IPIX radar and C-band radar for simulations, we can see that the model has a significant performance improvement for weak target detection compared to the traditional 3D-IFS algorithm. The detection probability of the model reaches 70% at the SCR near -10 dB, and signal processing time of the model is approximately 0.3 s at the SCR near -6 dB, thus it meets the requirement for low-observable (SCR > -8 dB) and radial velocity about 600 m/s high speed weak target detection in sea clutter.