According to the reconstruction feature of fluctuation-correlation ghost imaging (GI), we define a normalized characteristic matrix and the influence of the property of random coded patterns on GI is investigated based on the theory of matrix analysis. Both simulative and experimental results demonstrate that for different random coded patterns, the quality of fluctuation-correlation GI can be predicted by some parameters extracted from the normalized characteristic matrix, which suggests its potential application in the optimization of random coded patterns for GI system.

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Angle-only sensors cannot provide range information of targets and in order to determine accurate position of a signal source, one can connect distributed passive sensors with communication links and implement a fusion algorithm to estimate target position. To measure moving targets with sensors on moving platforms, most of existing algorithms resort to the filtering method. In this paper, we present two fusion algorithms to estimate both the position and velocity of moving target with distributed angle-only sensors in motion. The first algorithm is termed as the gross least square (LS) algorithm, which takes all observations from distributed sensors together to form an estimate of the position and velocity and thus needs a huge communication cost and a huge computation cost. The second algorithm is termed as the linear LS algorithm, which approximates locations of sensors, locations of targets, and angle-only measures for each sensor by linear models and thus does not need each local sensors to transmit raw data of angle-only observations, resulting in a lower communication cost between sensors and then a lower computation cost at the fusion center. Based on the second algorithm, a truncated LS algorithm, which estimates the target velocity through an average operation, is also presented. Numerical results indicate that the gross LS algorithm, without linear approximation operation, often benefits from more observations, whereas the linear LS algorithm and the truncated LS algorithm, both bear lower communication and computation costs, may endure performance loss if the observations are collected in a long period such that the linear approximation model becomes mismatch.

Underwater ghost imaging is an effective method of underwater detection. In this research, theoretical and experimental investigations were conducted on underwater ghost imaging, combining the underwater optical field transmission model with the inherent optical parameters of a water body. In addition, the Wells model and the approximate Sahu-Shanmugam(S-S) scattering phase function were used to create a model for underwater optical transmission. The second-order Glauber function of the optical field was then employed to analyze the scattering field degradation during the transmission process. The simulation and experimental results verified that the proposed underwater model could better reveal the degrading effect of a water body on ghost imaging. A further series of experiments comparing underwater ghost imaging at different detection distances was also conducted. Cooperative targets were imaged up to 65.2 m (9.3 attenuation lengths (ALs), attenuation coefficient c = 0.1426 m-1, and scattering coefficient b = 0.052 m-1) and non-cooperative targets up to 41.2 m (6.4 ALs, c = 0.1569 m-1, and b = 0.081 m-1). From equating the experimental maximum imaged AL for cooperative targets with Jerlov-I water (c = 0.048 m-1 and b = 0.002 m-1), the system has the maximum imaging distance of 193.7 m.

Underwater ghost imaging is an effective method of underwater detection. In this research, theoretical and experimental investigations were conducted on underwater ghost imaging, combining the underwater optical field transmission model with the inherent optical parameters of a water body. In addition, the Wells model and the approximate Sahu-Shanmugam(S-S) scattering phase function were used to create a model for underwater optical transmission. The second-order Glauber function of the optical field was then employed to analyze the scattering field degradation during the transmission process. The simulation and experimental results verified that the proposed underwater model could better reveal the degrading effect of a water body on ghost imaging. A further series of experiments comparing underwater ghost imaging at different detection distances was also conducted. Cooperative targets were imaged up to 65.2 m (9.3 attenuation lengths (ALs), attenuation coefficient c = 0.1426 m-1, and scattering coefficient b = 0.052 m-1) and non-cooperative targets up to 41.2 m (6.4 ALs, c = 0.1569 m-1, and b = 0.081 m-1). From equating the experimental maximum imaged AL for cooperative targets with Jerlov-I water (c = 0.048 m-1 and b = 0.002 m-1), the system has the maximum imaging distance of 193.7 m.