filter stability

Filter stability refers to a filter’s ability to produce consistent and accurate estimates over time without the output diverging or oscillating uncontrollably. In practical terms, a stable filter quickly adapts to incoming data and maintains reliable performance, providing steady results even as conditions change. If a filter is unstable, its estimates may become erratic or diverge, making its predictions unreliable. Ensuring stability is important for systems like navigation, tracking, or control processes, where dependable information is crucial for decision-making.