Beyond Stealth: How Chinese Military Research Aims to Neutralize Next-Generation Stealth Fighters

The evolution of China's air defense is shifting from upgrading individual hardware to creating an intelligent, predictive network architecture. As highlighted in a recent study by the PLA Air Force Engineering University, the goal is to overcome the limitations of current radars (such as those in operation in Iran), which often lose contact when a stealth aircraft changes attitude due to the dynamic and fluctuating nature of the radar cross-section (RCS). The new strategy is based on the creation of a closed-loop cognitive system that transforms detection into a calculable variable.

The JY-26 decimeter-wave warning radar (in English: Type JY-26 Warning Radar) is a newly developed three-dimensional ultra-high frequency (UHF) radar system created by China. It employs an advanced two-dimensional digital active phased array control system and features a detection range of 500 kilometers, high measurement accuracy, strong anti-jamming capabilities and mobility, high data transmission rates, high speed, and anti-stealth capabilities.

The first pillar of this technology is the move beyond generic statistical models through the creation of a "digital twin" of the target's radar signature. Using extremely detailed RCS databases, constructed using the physical optics (PO) method, researchers map the aircraft's reflectivity for every possible observation angle from 0° to 360°. This dynamic mapping makes it possible to understand how even a small change in course can suddenly make a stealth fighter visible to one of the network nodes.

The operational core of the system is the Joint Resource Allocation Algorithm (JBSPA), which enables the radar to "predict" the target's future state. By combining the aircraft’s predicted flight path with the positions of the radar nodes in the MIMO (Multiple-Input Multiple-Output) network, the system calculates the future observation angle and consults the RCS database to anticipate reflectivity peaks. In those critical moments, the central system directs the network’s radars to focus their beams and transmit power only where the contribution to tracking accuracy is greatest, optimizing resources and improving Low Probability of Interception (LPI) performance.

To ensure that the target remains "locked" even during evasive maneuvers or in the presence of interference, the network uses data fusion based on the Covariance Intersection (CI) algorithm. This method allows for the integration of tracks from different MIMO radars, providing a common upper bound on the error variance and ensuring stability even when the inter-covariances between nodes are unknown. Accuracy is measured using the Bayesian Cramér-Rao Lower Bound (BCRLB), with simulations indicating extremely fast response times—approximately 0.02 seconds per frame—meeting the requirements of real-time air defense.

From an intelligence perspective, future developments indicated by PLA research aim to expand this capability by integrating signal frequency and polarization. This approach seeks to exploit the "weakness" of radar-absorbing materials (RAM), whose performance varies drastically with changes in wave frequency. In this way, Chinese air defense seeks to transform stealth not only into a predictable factor, but into an exploitable vulnerability to guide weapon systems with millimeter-level precision.