Maritime Radar Target Detection in Presence of Strong Sea Clutter Based on Blind Source Separation

Glowworm Swarm Optimization and Its Application to Blind Signal Separation

“…Step 4. Update luciferin ( ) according to (1), confirm the set of neighbors ( ) according to (2), and compute the probability of movement ( ) according to (3).…”

“…The values of main parameters of MGSO are kept fixed in this experiment, and listed in Table 1. Figure 6 is the restored signals obtained by GMSO after 15 updates; Figure 7 is two-dimensional map of W (1, 1) and W (2,1) and approximately plots the track of glowworms seeking optimal solution. The fitness curves in Figure 8 mean that the standard PSO easily falls into a local optimum; the standard GSO has a good ability to search for the optimal value, but its convergence is not fast enough against others; MPSO has the best behavior on accuracy and speed.…”

“…It is the task of blind signal separation (BSS) to recover unknown independent source signals obtained from sensors. The BSS technology has received considerable attention in recent years because of its significant potential applications such as sonar and radar signal processing [1,2], wireless communication [3], geophysical exploration [4,5], biomedical signal processing [6,7], speech and image processing [8,9], and machine fault diagnosis [10,11]. BSS has two important components: the objective function and the optimization algorithm.…”

Polarimetric detection of maritime floating small target based on the Complex-valued Entropy Rate Bound Minimization

“…Polarimetry helps the radar to detect targets more accurately. In addition, some method based on other signal processing technique such as blind source separation (BSS) [ 22 , 23 ], independent component analysis (ICA) [ 24 ], and machine learning [ 25 , 26 , 27 ] are proposed for doing this detection task. Here, we utilized polarimetry to detect sea surface small floating target by employing one of complex-valued Independent Component Analysis (cICA) algorithm.…”

“…The proposed detector is flexible in a manner that one can choose any arbitrary length (time sample size) for separation and detection decision tasks. Other assumptions of the cICA can be used for radar signals, since as mentioned in [ 22 ], clutter and target signal are independent each other. In addition, they are non-circular and non-Gaussian distributed signals.…”