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In this article, we propose a new distributed sensors-based multi-target geolocation and tracking technique. The proposed technique is a joint time-of-arrival (TOA) and direction-of-arrival (DOA) factor graph (FG) for multi-target geolocation (FG-GE), which is further combined with another FG for extend Kalman filtering (FG-GE-EKF) for tracking. Two-dimensional (2D) and three-dimensional (3D) scenarios are considered. In the FG-GE part, a new sensor association technique is proposed to solve the matching problem, which makes the right correspondence between the DOA/TOA information gathered by the distributed sensors and each target. With the proposed sensor association technique, the measured signals from targets can adequately be matched to their corresponding FGs. Thereby, the multi-target geolocation can be reduced to multiple independent single target geolocation. In addition, in the 3D scenario, each target is projected onto three orthogonal planes in the (x, y, z) coordinate. With this operation, the 3D geolocation is decomposed into three 2D geolocation problems. In the FG-GE-EKF part, the whole tracking system can be divided into two steps: prediction step and update step. In the prediction step, the predicted state is obtained from the previous state. Then, we utilize the predicted state as a prior information, and also to update the message exchanged in FG-GE. In the update step, the estimates obtained by FG-GE are regarded as observation state which is used to refine the predicted state, and acquire the current state. With proposed the FG-GE-EKF, the position estimation accuracy and tracking performance can be improved dramatically, without requiring excessively high computational effort. INDEX TERMS Factor graph (FG), time of arrival (TOA), direction of arrival (DOA), geolocation, extend Kalman filter (EKF), tracking, sensor association.

The determination of the optimal measurement area of the articulated arm measuring machine belongs to the multi-dimensional function optimization problem under complex constraints. To realize high-precision measurement of low-precision articulated arm measuring machine, we analyze the working principle and error source of the measuring machine, and establish the optimization target model of the optimal measurement area in this paper. We propose a method for determining the optimal measurement area of an articulated arm measuring machine based on improved FOA. The basic FOA algorithm is improved, the historical optimal individual and population centroid information are added in the population iteration update process, and the fruit fly individuals in each iteration are directly used as the taste concentration judgment value, which increases cooperation and information sharing among fruit fly individuals, and improves the global optimization ability and stability of the algorithm. In the designated area of the measuring machine, we have carried out comparative experiments on the optimization results of improved FOA and basic FOA, ACO, PSO, AL-SC-FOA, LGMS-FOA, IPGS-FFO. Experimental results show that the improved FOA, ACO, PSO, and IPGS-FFO algorithms do not fall into local optimum, and the optimal measurement area determined by them is consistent with the optimization results of other algorithms, and is superior to other algorithms in convergence speed and stability, so it is more suitable for determining the optimal measurement area of articulated arm measuring machine.

In a complex environment, the long-time memory and coupling effect are two important system characteristics that can be described by the fractional damping force and coupling force. This paper investigates the collective behaviors of two coupled fractional harmonic oscillators driven by different frequency fluctuations, including stability, synchronization and stochastic resonance (SR). Theoretically, the ‘synchronization condition’ and ‘stability condition’ of the system are derived. Comparative analysis shows that the latter is stricter than the former. Based on this, an analytical expression of the output amplitude gain is obtained. The numerical results show that when the stability condition is met, the average trajectories of two particles are both bounded and synchronous. Otherwise, they will diverge to infinity. Increasing ɛ (coupling strength) and decreasing α (fractional order) can both accelerate the synchronization speed. SR mainly occurs in the high-α or high-σ (noise amplitude) region, which means that SR emergence can be controlled by adjusting α or σ. The damping force, coupling force and frequency fluctuations compete with each other; thus, the SR intensity should be maximized by adjusting α, ɛ and σ simultaneously.

Competition in the apparel market has developed from preliminary price competition, quality competition, and scale competition to the current state of brand competition. The phenomenon of brand overlap cannot be avoided by apparel enterprises during the process of building and manufacturing their brands. This paper has selected nine identification elements of three dimensions, which we used to construct an apparel brand overlap identification model. This model is based on the theories of customer perceived value and brand identity and was constructed by taking consumer perspectives as the starting point. Two apparel brands from the representative international E Company have been selected as our empirical research objects. An apparel brand overlap identification model has been constructed based on questionnaire analysis and a cognitive experiment involving eye-tracking technology. In addition, the overlap elements among apparel brands, as well as the cognitive situation of consumers with regard to brand overlap, have been analyzed.