1. Introduction
1.1 2-D Systems
1.2 Communication Constraints
1.3 Recent Progress on Filtering for 2-D Systems
1.4 Outline
2. Minimum-Variance Recursive Filtering for Two-Dimensional Systems with Degraded Measurements: Boundedness and Monotonicity
2.1 Problem Formulation
2.2 The Minimum-Variance Filter Design
2.3 Performance Analysis
2.4 Numerical Example
2.5 Summary
3. Robust Kalman Filtering for Two-Dimensional Systems with Multiplicative Noises and Measurement Degradations
3.1 Problem Formulation and Preliminaries
3.2 Upper Bound for The Generalized Error Variance
3.3 Suboptimal Filter Design
3.4 Numerical Example
3.5 Summary
4. Robust Finite-Horizon Filtering for Two-Dimensional Systems with Randomly Varying Sensor Delays
4.1 Problem Formulation
4.2 Preliminaries
4.3 Finite-Horizon Robust Kalman Filter Design
4.4 Numerical Example
4.5 Summary
5. Recursive Filtering for Two-Dimensional Systems with Missing Measurements subject to Uncertain Probabilities
5.1 Problem Formulation
5.2 Recursive Filter Design
5.3 Numerical Example
5.4 Summary
6. Resilient State Estimation for Two-Dimensional Shift-Varying Systems with Redundant Channels
6.1 Problem Formulation and Preliminaries
6.2 Resilient Filter Design
6.3 Numerical Examples
6.4 Summary
7. Recursive Distributed Filtering for Two-Dimensional Shift-Varying Systems Over Sensor Networks Under Random Access Protocols
7.1 Problem Formulation and Preliminaries
7.2 Main Results
7.3 Numerical Example
7.4 Summary
8. Resilient Filtering for Linear Shift-Varying Repetitive Processes under Uniform Quantizations and Round-Robin Protocols
8.1 Problem Formulation
8.2 Main Results
8.3 Numerical Example
8.4 Summary
9. Event-Triggered Recursive Filtering for Shift-Varying Linear Repetitive Processes
9.1 Problem Formulation
9.2 Main Results
9.3 Numerical Example
9.4 Summary
10. Conclusions and Future Topics