A programmable metasurface stamps temporal codes onto ambient radio waves, enabling passive radar to detect and track drones with active radar precision and zero dedicated transmission.
(Nanowerk Spotlight) Radar systems face a trade-off between stealth and capability. Active radars emit their own signals and achieve precise detection, but they consume power and reveal their position. Passive radars avoid both problems by eavesdropping on existing wireless transmissions and listening for echoes that bounce off targets. But without control over the illuminating signal, passive receivers struggle to separate faint target reflections from the direct transmission and co-channel interference that flood the receiver.
Small or slow-moving objects compound the difficulty. Conventional passive systems rely on Doppler frequency shifts to distinguish targets from background clutter, so anything that barely moves produces a signal too weak to extract.
A new study published in Advanced Science (“Metasurface-Enabled Active-Like Passive Radar”) addresses this problem by inserting a programmable metasurface between the ambient signal and the target, converting a passive radar into something that behaves like an active one without ever emitting a dedicated transmission.
The system, called a metasurface-enabled passive radar (MEPR), uses a flat panel of 768 subwavelength antenna elements arranged in a 32 × 24 grid, forming an aperture of roughly 0.78 × 0.59 m². Each element contains a PIN diode that switches between two reflection states, flipping the phase of incoming radio waves by 180°. A field-programmable gate array drives these switches at intervals of 2.5 microseconds, reconfiguring the surface’s reflection pattern fast enough to stamp distinct temporal codes onto different reflected beams.
Conceptual illustration of a MEPR system. (a) Overview of the MEPR used for detecting and tracking a UAV in a complex urban environment. The system consists of an STC-PM mounted on a building facade, two synchronized receivers (a reference and a surveillance channel), and a post-processing module. The STC-PM dynamically modulates ambient wireless signals in space and time, embedding distinct temporal tags that enable the separation of target echoes from environmental interference. (b) Schematic of the space-time modulation mechanism. The STC-PM converts incoming wireless signals into two tagged components: one defined by (c1,f1) to generate the reference signal y1(t) at receiver R1, and the other defined by (c2,f2) to produce the scanning signal y2(t) for the region of interest. The post-processing stage performs temporal code matching and cross-correlation between y1(t) and y2(t) to extract the target response. (c) Comparison with a conventional active radar, in which the transmitted waveform is known and coherently linked to the transmitter, allowing direct detection. (d) Comparison with a traditional PR lacking STC modulation, where direct-path and co-channel interference remain dominant, hindering the detection of weak or slow-moving targets. (Image: Reproduced from DOI:10.1002/advs.75629, CC BY) (click on image to enlarge)
The coding scheme is what separates the MEPR from a conventional passive receiver. The metasurface splits its output into two components. One beam carries a reference code and points toward a reference receiver. The other carries a different code and sweeps across the region of interest, illuminating potential targets. Because each beam has its own unique temporal tag, correlation processing at the receiver can isolate the target echo from everything else.
The underlying framework decomposes the metasurface response into spatial modes that control beam direction and temporal modes that control coding signatures. When the receiver cross-correlates the reference and surveillance channels, terms unrelated to the metasurface modulation average out. What remains is proportional to the target’s reflection, positioned at the correct delay, mimicking the output of an active radar transmitting its own coded waveform.
Simulations revealed a sharp dependence on coding length. With only one switching interval, equivalent to a conventional passive radar, the detection map showed heavy clutter and poor target discrimination. Performance improved steadily as the sequence grew longer. Once it exceeded roughly 50 switching intervals, the MEPR matched the azimuth resolution of an active radar with the same aperture size.
The team built a proof-of-concept prototype operating at 5.48 GHz and tested it in a cluttered indoor laboratory filled with metal cabinets and chairs. Three metallic letter-shaped targets placed one meter from the metasurface served as test objects. A scanning plane of 1.2 × 1.2 m² was sampled at 0.02 m resolution, producing a complete image in under one second. Reconstructed images sharpened progressively with increasing code length, matching theoretical predictions.
A separate experiment tested interference rejection directly. When the team introduced a second source of comparable power, the MEPR maintained clear target detection, confirming that temporal coding effectively rejected co-channel contamination even under aggressive conditions.
Tracking a flying drone put the concept under greater strain. Positioned in the far field of the metasurface, the unmanned aerial vehicle traced letter-shaped trajectories at a height of 3.3 m while the MEPR followed it in real time. A greedy-search algorithm performed a coarse scan to locate candidate regions, then refined the position through a local high-resolution pass, updating at roughly 0.8 seconds per frame. Average position errors measured 0.116 m without interference and 0.134 m with a second source active.
All experiments took place indoors under controlled conditions, and outdoor operation would introduce time-varying multipath effects and platform instability. The current implementation also requires a pre-acquired background map to subtract static clutter, a constraint that limits adaptability in rapidly changing scenes. Ambient signals typically offer narrower bandwidth than dedicated wideband radars, restricting range resolution compared to active systems.
By embedding programmable modulation directly into the propagation environment, the MEPR acquires active-like detection characteristics while preserving the low-power, transmitter-free nature of passive operation. The approach effectively turns the wireless infrastructure already blanketing urban areas into a sensing resource. Extending it to outdoor scenarios will require adaptive background modeling and distributed metasurface architectures capable of covering larger apertures, but the principle that ambient radio waves can be structured after emission, without cooperation from the source, opens a practical path toward scalable and energy-efficient radar sensing.
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