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To solve the problem that the traditional received signal strength indicator real-time location method does not test the attenuation characteristics of the electromagnetic wave transmission in the location area, which cannot guarantee the accuracy of the location, resulting in a large location error.

At present, the compressed sensing (CS) reconstruction algorithm can be roughly divided into the following two categories (Zhouzhou and Fubao, 2014; Lagunas et al., 2016): one is the greedy iterative algorithm proposed for combinatorial optimization problems, which includes matching pursuit algorithm (MP), positive cross matching tracking algorithm (OMP), greedy matching tracking algorithm, segmented orthogonal matching tracking algorithm (StOMP) and so on. The second kind is the convex optimization algorithm, which also called the optimization approximation method. The common method is the basic tracking algorithm, which uses the norm instead of the norm to solve the optimization problem. In this paper, based on the piecewise orthogonal MP algorithm, the improved StOMP reconstruction algorithm is obtained.

In this paper, the MP algorithm (OMP), the StOMP and the improved StOMP algorithm are used as simulation reconstruction algorithms to achieve the comparison of location performance. It can be seen that the estimated position of the target is very close to the original position of the target. It is concluded that the CS grid-based target stepwise location method in underground tunnel can accurately locate the target in such specific region.

In this paper, the offline fingerprint database in offline phase of location method is established and the measurement of the electromagnetic noise distribution in different localization areas is considered. Furthermore, the offline phase shares the work of the location process, which greatly reduces the algorithm complexity of the online phase location process and the power consumption of the reference node, meanwhile is easy to implement under the same conditions, as well as conforms to the location environment.

The purpose of this paper is to determine important attributes of processed food, consumers’ trust in different information resources, and the impact of trust, demographic and behavior variables on the preference of processed food attributes among Chinese consumers.

Data of 1,267 participants were collected from four cities in China. A five-point Likert scale was used to measure consumer preference for 12 juice attributes. Consumer trust in nine sources of information on product quality was measured. Cluster analysis was used to segment consumers into groups based on their preference for juice attributes and trust in information sources, respectively. A multinomial logistic model was used to determine the impact of trust, demographic and behavior variables on the preference of juice attributes.

Consumers rate manufacture date, taste and food safety labels as the most important attributes of fruit juice products. Among different information sources, consumers place more trust in private information sources and traditional media. The low trust in different information sources impedes consumer preference for processed food quality attributes.

This research is among the few that examine consumer preference for processed food, such as juice. It identifies four distinct preference groups and trust groups, respectively, based on consumer preference for juice attributes and trust in different information sources. This paper provides important information for processed food companies and policymakers to effectively enact marketing strategies in China.