  In this paper, the event-triggered resilient filtering problem is
investigated for a class of two-dimensional systems with asynchronous-delay
under binary encoding-decoding schemes with probabilistic bit flips. To reduce
unnecessary communications and computations in complex network systems,
alleviate network energy consumption, and optimize the use of network
resources, a new event-triggered mechanism is proposed, which focuses on
broadcasting necessary measurement information to update innovation only when
the event generator function is satisfied. A binary encoding-decoding scheme is
used in the communication process to quantify the measurement information into
a bit stream, transmit it through a memoryless binary symmetric channel with a
certain probability of bit flipping, and restore it at the receiver. In order
to utilize the delayed decoded measurement information that a measurement
reconstruction approach is proposed. Through generating space equivalence
verification, it is found that the reconstructed delay-free decoded measurement
sequence contains the same information as the original delayed decoded
measurement sequence. In addition, resilient filter is utilized to accommodate
possible estimation gain perturbations. Then, a recursive estimator framework
is presented based on the reconstructed decoded measurement sequence. By means
of the mathematical induction technique, the unbiased property of the proposed
estimator is proved. The estimation gain is obtained by minimizing an upper
bound on the filtering error covariance. Subsequently, through rigorous
mathematical analysis, the monotonicity of filtering performance with respect
to triggering parameters is discussed.
