Chinese scientists use open-source data to spot suspected Israeli electronic warfare units

Chinese military scientists claim they have developed an algorithm that could help identify electronic warfare units using civil aviation flight data.

The researchers said they had located two sources of interference that were spoofing their locations near Israel during the conflict with Iran.

The team did not explain why they had focused on the Israeli military.

The researchers estimated the locations of the two units as being near Haifa, with reported positioning errors between 10.9km and 18.9km (6.7-11.7 miles).

The South China Morning Post could not independently verify the claims.

The study, conducted by Du Lan and a team at the People’s Liberation Army’s Information Engineering University in Zhengzhou, was published online on October 7 in the peer-reviewed Journal of Geomatics Science and Technology.

The researchers analysed 43 days of aircraft-tracking data from open-source civil aviation systems, covering the period from February 27, the day before the US and Israel launched their attack on Iran, to April 10.

Electronic interference may result in aviation data that shows abrupt jumps to a distant location or movements inconsistent with a normal flight path.

The team’s algorithm used abnormal flight paths to estimate the possible locations of the sources of this interference.

“The method requires no additional monitoring equipment and is low-cost and timely,” the researchers wrote.

“It provides key technical support for civil aviation safety and situational awareness of spoofing interference in overseas conflict zones.”

The team identified two distinct areas in the Mediterranean. “Target area 1 was about 80km northwest of Haifa, a major city in northern Israel, while target area 2 was about 30km northwest of the Gaza Strip. Both target areas were in the Mediterranean Sea,” the authors wrote.

The researchers suggested that the different patterns could reflect attempts to counter different types of drone threats, although the intended targets could not be directly verified.

“The spoofing source corresponding to target area 1 is inferred to have mainly countered long-range suicide drones with some resistance to spoofing, such as Iran’s Shahed-136, requiring a more complex dynamic spoofing strategy,” Du and her team wrote.

“Target area 2 is inferred to have mainly countered low-cost, short-range drones used by groups in Gaza and the Houthi movement [from Yemen], whose resistance to navigation spoofing is weaker and which can be countered with a static, single-point spoofing strategy.”

Du and her team used publicly available aircraft position and speed data from the Automatic Dependent Surveillance-Broadcast system.

The researchers initially screened abnormal tracks using speed thresholds that were possible indicators that flight data was being spoofed.

They then applied additional time, location, altitude and operating-period constraints to filter out factors such as data errors, aircraft manoeuvres, low-altitude flights and sources of interference being switched on and off.

The team said future work would incorporate navigation data from ships to extend the method beyond civil aviation.