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Maximum Likelihood Function Indoor Positioning Algorithm Based on RSSD

At present, the research of indoor positioning is mainly based on active positioning, which means the transmitting node to be located can interact with the receiver. In this case, a higher positioning accuracy has been achieved. But in some cases, the power of the transmitter is unknown, which requires the study of passive positioning. Therefore, this paper proposes a maximum likelihood function method based on received signal strength difference (RSSD), which solves the problem that the source power is unknown power and reduces the complexity of the algorithm. The algorithm is tested in the laboratory with a length of 10.111m and a width of 6.129m. The test result shows that the positioning error is 1.2m when the CDF is less than 50%, and it is 2.09m when the CDF is less than 90%. Compared with the maximum likelihood function method based on received signal strength indicator (RSSI), the positioning accuracy of the algorithm is improved by 5% and the calculation amount of the algorithm is reduced by 70%.