## 1 Introduction  
The information obtained by satellites's sensors account for an increasing proportion of the total information obtained by humans. Then, the sensorweb proposed by NASA, has created an interoperable environment for a diverse set of satellite sensors via the use of software and the Internet. The authors of [1] point out that the development trend of sensorweb is integrating with other networks. The space information network is the high-level result of the further integration of sensorweb and space-based networks [2]. As a result of the sensorweb's evolution, the space information network is a network system that acquires, transmits, and processes space information in real-time based on a space platform (such as a synchronous satellite, a medium or low orbit spacecraft, a near space vehicle, a drone, a manned aircraft, etc.) [3]. With the construction and development of the space information network (SIN), several researches about space network models, network information theory, space information cognition, and space network security have been proposed [4, 5]. However,a comprehensive demonstration and verification systems for these new results are still urgently required. In recent years, a consensus has been formed on the Tracking and Data Relay Satellite System (TDRSS) as the backbone network of SIN [6]. As an integrated system in orbit, TDRSS is similar to the space information network to a certain extend regarding its structure, function, and service objects, which can provide a feasible method to the demonstration of space information network [7]. The comprehensive integrated demonstration platform built with TDRSS as the core can be used as a basic network architecture for the current demonstration of space network integration demonstration. It has the advantages of low implementation cost, strong demonstration ability, high scalability and flexibility. During the construction of a demonstration platform based on TDRSS, on the one hand, it is necessary to consider the evaluation of the demonstration platform itself. On the other hand, new technology test results need new evaluation models and method support. One or two indicators cannot meet the above needs. Therefore, comprehensive evaluation with multiple indicators for the demonstration platform needs to be studied and designed. The comprehensive evaluation study will face many problems. First, due to the wide range of technical fields involved in the demonstration platform itself and the diversity of applications of the demonstration, the platform-related indicators are numerous and diverse. Second, the attributes of some indicators might overlap, have strong correlation or even repetition, leading to coupling redundancy. Then, as a typical tree structure, the indicator system may have too many lower-level indicators, causing difficulties in adjusting the number of layers. Finally, the subjective scoring by people caused evaluation errors, which often made the evaluation results unacceptable. Especially when there are too large differences among the subjective scores, how to aggregate the opinions of the experts is also a problem. In the field of decision-making evaluation, the first three problems usually appear in the process of constructing the indicator system, and the last problem is common in the application process of the indicator system. The solution of the problem above in this paper is as follows. For the first three problems, we construct the index system layer by layer with the logical sequence. First, we use cluster analysis to achieve the classification and selection of indicators to determine the first level indicators (criteria layer). Then, we reconstruct the indicator system's levels to determine the second level indicators (element layer). Finally, the third level indicators are decomposed and optimized to remove coupled redundant indicators, which completes the index system.