Table 1 Event-triggered confidentiality fusion estimation against eavesdroppers algorithm

1: Input parameter: \(P^{\delta }\), \(\overline{\sigma }\), \(\underline{\sigma }\) \(\overline{P}\). Input system parameter A, C_i, Q, R_i, \(P_{i} (0)\), \(P_{ij} (0)\), \(\lambda_{i}\), \(\rho_{i}\) (i = 1, 2, 1,…, L);

2: for i: = 1 to L do

3: Step 1: Calculate the stable error covariance \(\overline{P}_{ii}\) of each local estimation system;

4: Step 2: Compute \(\frac{1}{{\lambda_{i} }}\left( {1 - \frac{1}{{\rho (A)^{2} }}} \right),\,\frac{1}{{\rho_{i} }}\left( {1 - \rho (A)^{{ - \frac{2}{L}}} } \right);\)

5: Step 3: Select event trigger thresholds \(\eta_{i}\) according to conditions (14)–(15), and feed back to each local sensor;

6: end for

7: Step 4: The user’s FC processes the received signal according to (4), and performs state fusion estimation according to formulas (5)–(9);

8: Step 5: Go to step (4) and continue to calculate the fusion estimate value at the next time