{"id":27289766,"date":"2026-10-08T16:41:19","date_gmt":"2026-10-08T14:41:19","guid":{"rendered":"https:\/\/migflug.com\/afterburner\/why-radar-cannot-detect-small-drones-rcs-micro-doppler-birds\/"},"modified":"2026-10-08T16:43:34","modified_gmt":"2026-10-08T14:43:34","slug":"why-radar-cannot-detect-small-drones-rcs-micro-doppler-birds","status":"publish","type":"post","link":"https:\/\/migflug.com\/afterburner\/fr\/why-radar-cannot-detect-small-drones-rcs-micro-doppler-birds\/","title":{"rendered":"DJI Phantom vs Pigeon: Why Radar Still Cannot Find Small Drones"},"content":{"rendered":"<style>.et_pb_title_container h1.entry-title { padding-top: 40px !important; }<\/style>\r\n<!-- mfsh:top -->\r\n\r\n<style>\r\n.mfsh-trigger{display:inline-flex;align-items:center;gap:10px;height:44px;padding:0 18px;margin:0 0 26px;border:2px solid 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It is a tidy story. It is also wrong, and the measurement literature has been saying so for a decade.<\/p>\r\n<p>A DJI Phantom 3 and a pigeon were never measured against each other until a group at the University of St Andrews flew both past the same calibrated radars in 2019. The drone won. Not by a little: the Phantom\u2019s modal radar cross-section came out around minus 20 decibels per square metre, a pigeon\u2019s has been measured at minus 28.2 at X-band. The quadcopter is the <em>bigger<\/em> radar target.<\/p>\r\n<p>So the drone is not invisible. Radar can see it perfectly well. The reason it keeps getting through is a far more uncomfortable answer: we spent fifty years deliberately teaching radar to throw away exactly this kind of target, and we were right to, until about 2015.<\/p>\r\n\r\n<div style=\"background:#f4f6f8;border-left:4px solid #5C91FF;padding:18px 22px;margin:26px 0\"><p style=\"margin:0 0 10px;font-weight:700;font-size:17px;color:#0d1117\">Quick Facts<\/p><p style=\"margin:5px 0\"><strong>DJI Phantom 4 radar cross-section:<\/strong> median 0.020 m\u00b2 at 9 GHz in an anechoic chamber, but ranging from 0.004 m\u00b2 to 0.27 m\u00b2 depending purely on viewing angle<\/p><p style=\"margin:5px 0\"><strong>Measured in flight:<\/strong> Phantom 3 around \u221220 dBsm, Harris Hawk \u221222, Tawny Eagle \u221219 \u2014 the eagle out-returns the drone<\/p><p style=\"margin:5px 0\"><strong>Scattering regime:<\/strong> at X-band and above a 25\u201335 cm quadcopter is in the optical region, not the Rayleigh region<\/p><p style=\"margin:5px 0\"><strong>Range penalty:<\/strong> detection range scales with the fourth root of radar cross-section, so a 1,000-fold smaller target costs only a factor of 5.6 in range<\/p><p style=\"margin:5px 0\"><strong>Geometry penalty:<\/strong> an L-band air-surveillance radar with a 470 km instrumented range has a beam-intersection range of 690 m against a target at 60 m altitude<\/p><p style=\"margin:5px 0\"><strong>Bird overlap:<\/strong> 95 per cent of birds have a radar cross-section below 0.16 m\u00b2; small drones sit between 0.001 and 0.1 m\u00b2. Both fly below 30 m\/s<\/p><\/div>\r\n\r\n<h2 style=\"padding-top:22px\">The drone is not invisible<\/h2>\r\n<p>Start with the numbers, because almost everything written about this subject gets them wrong by an order of magnitude or three.<\/p>\r\n<p>The most systematic open dataset comes from a Czech team who put ten drone types on a turntable in an anechoic chamber at 9 GHz, calibrated against a 300 mm steel sphere. A DJI Phantom 4 returned a median of 0.020 m\u00b2. A hexacopter-class DJI F550 managed 0.030 m\u00b2. Even the tiny Yuneec Mantis, 190 mm across, came in at 0.004 to 0.006 m\u00b2.<\/p>\r\n<p>A separate group measured six DJI airframes in a compact-range chamber at Ku and K band in both polarisations. A Mavic Pro averaged minus 17 dBsm \u2014 about 0.02 m\u00b2. A Phantom 4 Pro, minus 15 dBsm, around 0.032 m\u00b2.<\/p>\r\n<p>These are small targets. They are not vanishingly small. The figure of 0.0001 m\u00b2 that circulates in trade coverage does not appear in the measurement literature as a drone value at all \u2014 it turns up as the extreme low tail of instantaneous fluctuation, as a back-scaled model, or as the measured cross-section of a bat. And the 0.01 m\u00b2 that appears on radar datasheets as \u201cthe\u201d small-drone figure is a convention the industry agreed on, not a measurement of any particular aircraft at any particular angle.<\/p>\r\n\r\n<figure class=\"wp-block-image size-large\" style=\"margin:0 0 24px;width:100%\"><img decoding=\"async\" class=\"skip-lazy\" data-no-lazy=\"1\" loading=\"eager\" width=\"1024\" src=\"https:\/\/migflug.com\/afterburner\/wp-content\/uploads\/sites\/4\/2026\/10\/dji-phantom-2-vision-plus-quadcopter.jpg\" alt=\"A DJI Phantom 2 Vision+ quadcopter\" style=\"width:100%;height:auto;max-width:100%;display:block\"><figcaption style=\"font-size:13px;color:#777;text-align:center;margin-top:6px;font-style:italic\">A DJI Phantom 2 Vision+ \u2014 the exact airframe used in two of the published radar cross-section studies. Most of it is plastic; the radar return comes from the battery, the motors and the wiring harness inside. Photo: David J \/ CC BY 2.0<\/figcaption><\/figure>\r\n\r\n<h2 style=\"padding-top:22px\">The bird is not a disguise. It is a twin<\/h2>\r\n<p>In 2019 Samiur Rahman and Duncan Robertson at St Andrews did the experiment everyone had been citing second-hand: they flew three DJI drones and four birds of prey past the same FMCW radars, at 24 GHz and 94 GHz, calibrated against a known trihedral. Not simulations, not chamber models \u2014 live targets, at 70 to 100 metres, with a falconry centre supplying the birds.<\/p>\r\n<p>The results demolish the clich\u00e9. Average modal radar cross-section at 24 GHz: Phantom 3 Standard, minus 20 dBsm. Inspire 1, minus 15. S900 hexacopter, minus 8. Northern Hawk Owl, minus 30. Harris Hawk, minus 22. Indian Eagle Owl, minus 21. Tawny Eagle, minus 19.<\/p>\r\n<p>Read the ordering. The Phantom sits <em>above<\/em> the hawk and far above the owl, and the largest bird in the test returns more than the smallest drone. More damaging still is the spread. The Phantom\u2019s 10th-to-90th-percentile band runs from minus 29.5 to minus 12 dBsm. The Indian Eagle Owl\u2019s runs from minus 30 to minus 12.5. Those are, to within rounding, the same interval.<\/p>\r\n\r\n<div style=\"background:#f8f9fa;border-left:4px solid #5C91FF;padding:20px 22px;margin:18px 0 24px;font-size:16px;line-height:1.7\"><em>&ldquo;However, due to the similarity in RCS values of the drones and birds, RCS values on their own cannot be reliably used for discriminating a drone from a bird. Other features of the targets (i.e. micro-Doppler) must be used along with the RCS information to achieve robust classification.&rdquo;<\/em><div style=\"margin-top:10px;font-size:14px;color:#555\"><strong>Samiur Rahman and Duncan A. Robertson<\/strong> &mdash; SUPA School of Physics and Astronomy, University of St Andrews, IET Radar, Sonar &amp; Navigation, 2019<\/div><\/div>\r\n\r\n<p>A Chinese team reached the same conclusion from the other direction, calculating that the maximum detectable ranges of a pigeon and a drone on their radar were 12 km and 11 km respectively. And Polish radar engineers writing for NATO put the scale of the nuisance in one line: 95 per cent of birds have a radar cross-section smaller than 0.16 m\u00b2, which means the bird population\u2019s range of returns entirely contains the drone population\u2019s. Assuming one bird per square kilometre, they note, there would be more than 1,200 birds within 20 km of a radar.<\/p>\r\n<p>Every one of them is a candidate drone.<\/p>\r\n<h2 style=\"padding-top:22px\">Why there is no single number<\/h2>\r\n<p>Here the physics gets interesting, and the popular explanation gets abandoned entirely.<\/p>\r\n<p>The standard line is that a drone is too small relative to the radar wavelength \u2014 that it sits in the Rayleigh scattering region where return falls off with the fourth power of size. At X-band and above, this is simply false. Using the thresholds in Knott\u2019s chapter of the Radar Handbook, a 35 cm quadcopter has a ka value of about 34 at 9.4 GHz, deep into the optical region, where anything above ka of 10 lies. Rahman and Robertson say it outright from their measurements: at K-band and W-band, drones and birds fall in the optical scattering region.<\/p>\r\n<p>In the optical region, return scales roughly with projected area. The drone\u2019s problem is not that it is electrically small. It is that it is <em>physically<\/em> small \u2014 a few hundred square centimetres of actual reflecting structure, most of it hidden inside a plastic shell.<\/p>\r\n<p>And what reflects is not the shell. The armasuisse group modelling a Phantom 2 found significant differences when the battery pack was left out of the model, with the motors treated as solid copper and the cable harness contributing substantially. A millimetre-wave study of nine airframes found the frame dominates for carbon-fibre builds \u2014 carbon fibre is conductive, and plastic-framed drones measured about 7 dB below carbon-fibre ones. The propellers barely matter for detection: rotating elements are at least 20 to 25 dB weaker than the main body.<\/p>\r\n<p>The consequence is that the echo is an interference pattern between a handful of small metal objects, and it swings violently with aspect. That Phantom 4 with its tidy 0.020 m\u00b2 median ranges from 0.004 to 0.27 m\u00b2 across viewing angles at a single frequency \u2014 a factor of about 70, or 18 dB. Any datasheet quoting one number for a drone is quoting a convention.<\/p>\r\n\r\n<figure class=\"wp-block-image size-large\" style=\"margin:0 0 24px;width:100%\"><img decoding=\"async\" class=\"skip-lazy\" data-no-lazy=\"1\" loading=\"eager\" width=\"1024\" src=\"https:\/\/migflug.com\/afterburner\/wp-content\/uploads\/sites\/4\/2026\/10\/rf-anechoic-chamber-pyramidal-absorber.jpg\" alt=\"A radio-frequency anechoic chamber lined with pyramidal absorber\" style=\"width:100%;height:auto;max-width:100%;display:block\"><figcaption style=\"font-size:13px;color:#777;text-align:center;margin-top:6px;font-style:italic\">An RF anechoic chamber. Every reliable drone radar cross-section figure in the literature was produced in a room like this, on a turntable, with the walls engineered to return nothing. Photo: Wikimedia Commons<\/figcaption><\/figure>\r\n\r\n\r\n<div style=\"position:relative;padding-bottom:56.25%;height:0;overflow:hidden;margin:24px 0\"><iframe class=\"skip-lazy\" data-no-lazy=\"1\" loading=\"eager\" src=\"https:\/\/www.youtube.com\/embed\/mvFCjX1HHGo\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;border:0\" allowfullscreen><\/iframe><\/div>\r\n\r\n<p style=\"font-size:13px;color:#777;text-align:center;margin:-10px 0 24px;font-style:italic\">The underlying signal-processing concepts \u2014 Doppler, MTI and clutter rejection \u2014 that the rest of this article turns on.<\/p>\r\n<h2 style=\"padding-top:22px\">The fourth root is not the villain<\/h2>\r\n<p>Radar detection range scales with the fourth root of radar cross-section. This is usually presented as the reason small drones defeat radar, and it is worth doing the arithmetic because it argues the opposite.<\/p>\r\n<p>A thousand-fold reduction in cross-section \u2014 30 dB \u2014 costs a factor of 1,000 to the power of one quarter, which is 5.62. A peer-reviewed study of an L-band air-surveillance radar published relative range factors that agree exactly: a minus 30 dBsm target is detected at 0.178 of the range of a 1 m\u00b2 target.<\/p>\r\n<p>Turn that around. A radar that holds a 1 m\u00b2 target at 50 km still holds a 0.001 m\u00b2 target at 8.9 km. For defending an airfield perimeter, that is not merely adequate, it is generous. Raw sensitivity is not what is failing.<\/p>\r\n<h2 style=\"padding-top:22px\">Geometry is the villain<\/h2>\r\n<p>The same study, examining an L-band AESA air-surveillance radar with a published instrumented range of 470 km, produced the most startling number in this entire subject.<\/p>\r\n<p>With the antenna 30 metres up and the beam on the horizon, the radar horizon against a target at 60 m altitude is 54.5 km. Tilt the beam up by 2.5 degrees \u2014 as you must, to look at the airspace a surveillance radar exists to watch \u2014 and the beam axis now intersects 60 m altitude at <strong>690 metres<\/strong>. At 20 degrees of elevation, 80 metres.<\/p>\r\n<p>A national air-defence radar built to see a fighter 470 km away cannot be pointed at a quadcopter creeping along at rooftop height more than a few hundred metres from its own mast. Not for want of power. The beam is simply somewhere else.<\/p>\r\n\r\n<div style=\"background:#f8f9fa;border-left:4px solid #5C91FF;padding:20px 22px;margin:18px 0 24px;font-size:16px;line-height:1.7\"><em>&ldquo;Two geometric limitations dominate. With near-horizontal beams, coverage is bounded mainly by the radar horizon. With positive-elevation beams, low-altitude coverage quickly becomes beam-intersection-limited at ranges that may be orders of magnitude shorter than the horizon distance. These constraints are physical and cannot be removed by signal processing alone.&rdquo;<\/em><div style=\"margin-top:10px;font-size:14px;color:#555\"><strong>Braun and Hegyi<\/strong> &mdash; Sensors, 2026, on the detection limits of a long-range L-band air surveillance radar<\/div><\/div>\r\n\r\n<h2 style=\"padding-top:22px\">And the filter is the real villain<\/h2>\r\n<p>Point the beam low and you buy the other problem. Clutter \u2014 terrain, buildings, vegetation, wind turbines, vehicles, rain \u2014 can return thousands of times more energy than the target hidden inside it.<\/p>\r\n<p>Radar solved this decades ago with Moving Target Indication: reject everything whose radial velocity is near zero, keep what is moving. It works beautifully against hills and car parks. It also happens to describe a hovering quadcopter exactly. At 1.5 GHz, one metre per second of radial velocity produces ten hertz of Doppler shift. A drone hovering over a runway threshold, or flying a crosswise track so its radial velocity is near zero, produces single-digit hertz. It lands inside the clutter notch \u2014 the band of Doppler frequencies the radar has been deliberately engineered to discard.<\/p>\r\n<p>Radar engineers at Poland\u2019s PIT-RADWAR put the trap in a single sentence to a NATO audience, and it is the thesis of this whole article.<\/p>\r\n\r\n<div style=\"background:#f8f9fa;border-left:4px solid #d32f2f;padding:20px 22px;margin:18px 0 24px;font-size:16px;line-height:1.7\"><em>&ldquo;A (legacy) radar designed to reject birds on the basis of radial velocity (and, possibly, RCS) will also suppress detections from LSS objects.&rdquo;<\/em><div style=\"margin-top:10px;font-size:14px;color:#555\"><strong>Micha\u0142 Meller and Tomasz Rutkowski<\/strong> &mdash; PIT-RADWAR S.A., Warsaw, NATO STO-MP-SET-311<\/div><\/div>\r\n\r\n<p>For fifty years, slow and low and small meant birds, lorries, trees and weather. Suppressing them was not an oversight; it was the single most valuable thing a radar could do. Their same paper warns that upgrading an existing radar to find low, slow, small targets may be very difficult and require substantial tradeoffs. The installed base of air-surveillance radar across Europe was optimised, correctly, for a world that ended around 2015.<\/p>\r\n<p>An academic at the Oxford Thermofluids Institute, asked last November why European airports kept closing, chose his words with more precision than most of the coverage that quoted him.<\/p>\r\n\r\n<div style=\"background:#f8f9fa;border-left:4px solid #5C91FF;padding:20px 22px;margin:18px 0 24px;font-size:16px;line-height:1.7\"><em>&ldquo;Many of the drones used are so small and light that a standard radar is not configured to detect them.&rdquo;<\/em><div style=\"margin-top:10px;font-size:14px;color:#555\"><strong>Dr David Bacci<\/strong> &mdash; Senior research assistant, Oxford Thermofluids Institute, speaking to Euronews, 20 November 2025<\/div><\/div>\r\n\r\n<p><em>Not configured to.<\/em> Not incapable of.<\/p>\r\n\r\n<figure class=\"wp-block-image size-large\" style=\"margin:0 0 24px;width:100%\"><img decoding=\"async\" class=\"skip-lazy\" data-no-lazy=\"1\" loading=\"eager\" width=\"1024\" src=\"https:\/\/migflug.com\/afterburner\/wp-content\/uploads\/sites\/4\/2026\/10\/small-drone-against-cloud-baltic-trust-2026.jpg\" alt=\"A small drone seen as a dark speck against cloud over a military range\" style=\"width:100%;height:auto;max-width:100%;display:block\"><figcaption style=\"font-size:13px;color:#777;text-align:center;margin-top:6px;font-style:italic\">A target drone over the range at Exercise Baltic Trust 2026, where NATO, allied and industry teams tested counter-drone systems. At a few hundred metres it is a speck against cloud \u2014 and to a radar built for airliners, exactly the kind of slow, low return the clutter filter was designed to throw away. Photo: U.S. Army<\/figcaption><\/figure>\r\n\r\n<h2 style=\"padding-top:22px\">Micro-Doppler, and what it cannot do<\/h2>\r\n<p>There is a real answer, and it is elegant. A drone\u2019s rotors spin at roughly 100 revolutions per second, and each blade modulates the return into sidebands and into a ladder of horizontal stripes on a spectrogram known as HERM lines. A bird flaps at 4 to 6 hertz. Two orders of magnitude apart.<\/p>\r\n<p>Better still, the HERM line spacing equals rotation rate times blade count, and is independent of the radar frequency \u2014 so a radar can read a drone\u2019s rotor speed and number of blades straight off the spectrogram. Convolutional neural networks trained on this have reported testing accuracies of 94.4 per cent across four classes and 98.3 per cent for the simple drone or not-a-drone question.<\/p>\r\n\r\n<div style=\"position:relative;padding-bottom:56.25%;height:0;overflow:hidden;margin:24px 0\"><iframe class=\"skip-lazy\" data-no-lazy=\"1\" loading=\"eager\" src=\"https:\/\/www.youtube.com\/embed\/9MDwQKvM_3g\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;border:0\" allowfullscreen><\/iframe><\/div>\r\n\r\n<p style=\"font-size:13px;color:#777;text-align:center;margin:-10px 0 24px;font-style:italic\">The cleanest demonstration of the micro-Doppler principle: a vibrating tuning fork written into a radar spectrogram.<\/p>\r\n<p>Now the caveats, because the 99 per cent figures come from laboratories.<\/p>\r\n<p>The micro-Doppler signature sits 20 to 30 dB below a bulk return that is already around minus 20 dBsm. It needs dwell time a surveillance radar sharing its attention across a full scan may not have. The UCL group that has done much of this work is candid that their results came from ideal conditions with a hovering drone of the same type at short ranges to maximise signal-to-noise, and that an unknown model flying erratically to evade detection will likely have a much reduced classification success rate.<\/p>\r\n<p>Aspect ruins it: at middling elevation angles the body shadows the rear rotors and the HERM lines collapse. Hexacopters produce a confused pattern as six rotors\u2019 contributions overlap. You cannot optimise pulse repetition frequency for blade flash and HERM lines simultaneously. And a gliding bird produces no wingbeat modulation at all \u2014 which makes it, to a classifier, indistinguishable from a drone that has stopped its rotors.<\/p>\r\n<p>Most soberingly, one peer-reviewed field study simply failed to find the effect: identifiable micro-Doppler signatures cannot be obtained in our radar data, its authors reported, despite expecting them from both wingbeat and blade rotation.<\/p>\r\n\r\n<div style=\"position:relative;padding-bottom:56.25%;height:0;overflow:hidden;margin:24px 0\"><iframe class=\"skip-lazy\" data-no-lazy=\"1\" loading=\"eager\" src=\"https:\/\/www.youtube.com\/embed\/2Srcb4SssKA\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;border:0\" allowfullscreen><\/iframe><\/div>\r\n\r\n<p style=\"font-size:13px;color:#777;text-align:center;margin:-10px 0 24px;font-style:italic\">A fidget spinner stood in for a rotor: the same physics that lets a radar count a drone\u2019s blades.<\/p>\r\n<p>There is a nice irony in who solved this best. The Dutch company whose radars now sit on military bases across Europe began as a bird-radar firm, built to keep flocks away from airports. Its founder has been direct about where the advantage came from.<\/p>\r\n\r\n<div style=\"background:#f8f9fa;border-left:4px solid #5C91FF;padding:20px 22px;margin:18px 0 24px;font-size:16px;line-height:1.7\"><em>&ldquo;Since we came from the bird-radar world, in which there are always huge amount of birds in the air, that was no challenge for us.&rdquo;<\/em><div style=\"margin-top:10px;font-size:14px;color:#555\"><strong>Siete Hamminga<\/strong> &mdash; Founder and CEO, Robin Radar Systems<\/div><\/div>\r\n\r\n<p>One more thing worth noticing about the counter-UAS radar market: essentially no manufacturer publishes a detection range against a stated radar cross-section. They publish instrumented range, or range against named drone classes. Blighter is a rare exception and its numbers are instructive \u2014 a nano-quadcopter out to 3 km, a walking person out to 5 km. A human being on foot is an easier radar target than a drone.<\/p>\r\n<h2 style=\"padding-top:22px\">So they stopped fighting the physics<\/h2>\r\n<p>Faced with all this, the practical answer for a decade was to give up on seeing the drone and listen for its pilot instead. Radio-frequency detection picks up the control link, and a US Department of Transportation audit of the FAA\u2019s airport trials found radar and radio frequency were the two most common methods, with electro-optics and acoustics trailing.<\/p>\r\n<p>That audit also found the limits. Airport radio spectrum is congested, which made detection difficult and, in some instances, not possible. Sensor coverage distance limited how well a drone could be located. Operators spent a lot of manpower discerning false positives. Technical readiness was low. This was a government auditor describing detection \u2014 not interception \u2014 as the binding constraint, and it was published in 2022.<\/p>\r\n<p>Then two things broke the radio-frequency half of the answer.<\/p>\r\n<p>The first was competence. When drones were repeatedly flown over Belgian military sites in late 2025, the defence minister described the failure on the record.<\/p>\r\n\r\n<div style=\"background:#f8f9fa;border-left:4px solid #5C91FF;padding:20px 22px;margin:18px 0 24px;font-size:16px;line-height:1.7\"><em>&ldquo;The security services\u2019 jammer didn\u2019t work because they tested our radio frequency and they changed frequency. They have their own frequencies. An amateur doesn\u2019t know how to do that.&rdquo;<\/em><div style=\"margin-top:10px;font-size:14px;color:#555\"><strong>Theo Francken<\/strong> &mdash; Belgian Minister of Defence, speaking to Euronews, 3 November 2025<\/div><\/div>\r\n\r\n<p>The second was fibre optics. Since emerging at scale in Russia\u2019s Kursk region in August 2024, spooled fibre-optic control cables thinner than fishing line \u2014 standard models beyond 30 km, some Ukrainian units reaching around 40 \u2014 have spread across the front. A drone trailing a glass thread has no radio link to jam, and, by the same token, nothing for a radio-frequency sensor to hear. The countermeasures being improvised against them are telling: shotguns, physical barriers, radar tripwires, acoustic sensors. The problem goes straight back to radar and optics.<\/p>\r\n\r\n<figure class=\"wp-block-image size-large\" style=\"margin:0 0 24px;width:100%\"><img decoding=\"async\" class=\"skip-lazy\" data-no-lazy=\"1\" loading=\"eager\" width=\"1024\" src=\"https:\/\/migflug.com\/afterburner\/wp-content\/uploads\/sites\/4\/2026\/10\/radar-cross-section-measurement-styrofoam-mount.jpg\" alt=\"A missile airframe mounted on styrofoam supports at a radar cross-section measurement facility\" style=\"width:100%;height:auto;max-width:100%;display:block\"><figcaption style=\"font-size:13px;color:#777;text-align:center;margin-top:6px;font-style:italic\">A Sergeant missile on styrofoam supports at a radar cross-section measurement range \u2014 the same technique, and very nearly the same furniture, that the drone measurement papers use today. Photo: U.S. Army<\/figcaption><\/figure>\r\n\r\n<h2 style=\"padding-top:22px\">Which is how we ended up shooting rockets at toys<\/h2>\r\n<p>If you cannot reliably detect the thing, and you cannot reliably jam it, what is left is making sure that the moment you <em>do<\/em> see it, killing it is cheap.<\/p>\r\n<p>Hence the APKWS laser-guided rocket, a guidance kit bolted onto an unguided Hydra-70. The Pentagon placed an initial order worth 322 million dollars against a 1.7 billion dollar ceiling in December 2025 for tens of thousands of rounds, at a per-shot cost reported at 24,900 dollars \u2014 against an AIM-9 that can exceed half a million. Hence high-power microwave, where one manufacturer reported disabling all 61 drones flown at a live-fire demonstration, including a 49-drone swarm.<\/p>\r\n<p>But cheap interceptors are a reply to the economics, not to the detection problem. And even a cheap interceptor runs into the same wall the Belgian minister described in his next breath: over a military base you can shoot a drone down, but nearby you have to be careful, because it can fall on a house, a car, a person.<\/p>\r\n<p>So the honest summary is not that drones are invisible to radar. A Phantom returns more energy than a pigeon and rather more than most owls. Radar can see it.<\/p>\r\n<p>The trouble is that we spent half a century building a sensor network whose beams point at airliner altitudes and whose filters are tuned to discard everything slow, low and small \u2014 because for fifty years, everything slow, low and small was a bird. That was the correct engineering decision for every year until roughly the one in which a consumer quadcopter became something you could buy for the price of a mobile phone. Unlearning it is turning out to be expensive.<\/p>\r\n<p><em>Sources: Rahman and Robertson, In-flight RCS measurements of drones and birds at K-band and W-band, IET Radar Sonar &amp; Navigation 13(11), 2019, and Radar micro-Doppler signatures of drones and birds, Scientific Reports 8:17396, 2018; Sedivy and Nemec, Drone RCS Statistical Behaviour, NATO STO-MP-MSG-SET-183; Ezuma et al., Radar Cross Section Based Statistical Recognition of UAVs at Microwave Frequencies, 2021; Schr\u00f6der et al., IEEE Radar Conference 2015; Semkin et al., IEEE Access, 2020; Patel, Fioranelli and Anderson, IET Radar Sonar &amp; Navigation 12(9), 2018; Gong et al., Progress In Electromagnetics Research M 81, 2019; Meller and Rutkowski, NATO STO-MP-SET-311; Braun and Hegyi, Sensors 26(13), 2026; Knott, Radar Cross Section, in Skolnik (ed.), Radar Handbook; Ritchie, Horne and Peters, UCL; US DOT Office of Inspector General report AV2022026, 30 March 2022; Euronews, 3 and 20 November 2025; Atlantic Council UkraineAlert, 24 February 2026; Air &amp; Space Forces Magazine, 10 December 2025; Blighter A800 Mk 2 datasheet; Robin Radar Systems product literature.<\/em><\/p>\r\n<!-- mfsh:bottom -->\r\n\r\n<button type=\"button\" class=\"mfsh-trigger mfsh-bottom\" data-mfsh-placement=\"bottom\" aria-haspopup=\"dialog\"><svg><use href=\"#mfsh-i-share\"\/><\/svg>Share this story<\/button>\r\n\r\n<!-- \/mfsh:bottom -->\r\n\r\n<style>.mfq{margin:34px 0 8px}.mfq h2{font:26px\/1.3 \"Gilroy semiBold\",Helvetica,Arial,sans-serif;color:#0d1117;padding-top:22px;margin:0 0 6px}.mfq .qa details{border-top:1px solid #5C91FF;margin:0;padding:0}.mfq .qa details:last-of-type{border-bottom:1px solid #e2e7ee}.mfq .qa summary{cursor:pointer;list-style:none;display:flex;justify-content:space-between;align-items:center;gap:16px;padding:22px 26px;font:18px\/1.7 \"Gilroy semiBold\",Helvetica,Arial,sans-serif;color:#0d1117}.mfq .qa summary::-webkit-details-marker{display:none}.mfq .qa summary::after{content:\"+\";font:24px Helvetica,sans-serif;color:#3568e0;flex:0 0 auto}.mfq .qa details[open] summary::after{content:\"\\2013\"}.mfq .qa details:hover summary{color:#3568e0}.mfq .qa .a{font:16px\/1.7 \"Gilroy regular\",Helvetica,Arial,sans-serif;color:#454e5e;padding:0 26px 24px}.mfq .qa .a a{color:#3568e0}@media(max-width:680px){.mfq .qa summary{padding:18px 14px;font-size:17px}.mfq .qa .a{padding:0 14px 20px}}<\/style>\r\n\r\n\r\n<section class=\"mfq\"><h2>Frequently Asked Questions<\/h2><div class=\"qa\"><details open><summary>Can radar detect small drones?<\/summary><div class=\"a\">Yes. Measured radar cross-sections for Phantom and Mavic-class quadcopters cluster around 0.01 to 0.1 square metres, which is a detectable target. The common claim that drones are too small for radar is not supported by the measurement literature. The difficulty is where radar beams point and what radar filters are designed to discard, not raw sensitivity.<\/div><\/details><details><summary>What is the radar cross-section of a DJI Phantom?<\/summary><div class=\"a\">It depends entirely on viewing angle, and no single number is honest. Chamber measurements at 9 GHz give a DJI Phantom 4 a median of 0.020 square metres, but values range from 0.004 to 0.27 square metres across aspect angles \u2014 a factor of about 70 at one frequency. In flight at 24 GHz a Phantom 3 measured around minus 20 dBsm.<\/div><\/details><details><summary>Do drones have a smaller radar cross-section than birds?<\/summary><div class=\"a\">Generally no. In the only study to measure both in flight with the same calibrated radars, a DJI Phantom 3 at minus 20 dBsm returned more than a Harris Hawk at minus 22 and far more than a Northern Hawk Owl at minus 30. Only the largest bird tested, a Tawny Eagle, out-returned the drone.<\/div><\/details><details><summary>Why is it hard to tell a drone from a bird on radar?<\/summary><div class=\"a\">Because their radar cross-section distributions overlap almost completely. A Phantom 3 spans minus 29.5 to minus 12 dBsm between the 10th and 90th percentiles; an Indian Eagle Owl spans minus 30 to minus 12.5. Both fly below 30 metres per second. Cross-section and speed cannot separate them, so classification depends on micro-Doppler.<\/div><\/details><details><summary>What is micro-Doppler and how does it identify drones?<\/summary><div class=\"a\">Spinning rotors modulate the radar return into sidebands and into evenly spaced spectrogram stripes called HERM lines. A drone rotor turns at roughly 100 hertz while a bird flaps at 4 to 6 hertz, so the two are easily distinguished in principle. HERM line spacing equals rotation rate times blade count and is independent of radar frequency.<\/div><\/details><details><summary>Why does a long-range air defence radar miss a low-flying drone?<\/summary><div class=\"a\">Geometry, not sensitivity. A published analysis of an L-band air-surveillance radar with a 470 km instrumented range found that with the beam tilted 2.5 degrees up, the beam axis intersects 60 metres altitude at just 690 metres range. The beam passes over low-flying targets, and no signal processing can fix that.<\/div><\/details><details><summary>Why do counter-drone systems use jammers instead of radar?<\/summary><div class=\"a\">Radio-frequency detection listens for the drone\u2019s control link, which is cheaper and simpler than fighting the radar physics. A 2022 US Department of Transportation audit found radar and radio frequency were the two most common detection methods at airports, though it also found airport spectrum congestion made detection difficult or impossible in places.<\/div><\/details><details><summary>Can fibre-optic drones be jammed or detected by radio?<\/summary><div class=\"a\">No. A drone flown on a spooled glass fibre, a technique that spread rapidly after appearing in the Kursk region in August 2024, has no radio control link. There is nothing to jam and nothing for a radio-frequency sensor to hear, which pushes the detection problem back onto radar, optical and acoustic sensors.<\/div><\/details><\/div><\/section>\r\n\r\n\r\n<script type=\"application\/ld+json\">{\"@context\":\"https:\/\/schema.org\",\"@type\":\"FAQPage\",\"mainEntity\":[{\"@type\":\"Question\",\"name\":\"Can radar detect small drones?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Yes. Measured radar cross-sections for Phantom and Mavic-class quadcopters cluster around 0.01 to 0.1 square metres, which is a detectable target. The common claim that drones are too small for radar is not supported by the measurement literature. The difficulty is where radar beams point and what radar filters are designed to discard, not raw sensitivity.\"}},{\"@type\":\"Question\",\"name\":\"What is the radar cross-section of a DJI Phantom?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"It depends entirely on viewing angle, and no single number is honest. Chamber measurements at 9 GHz give a DJI Phantom 4 a median of 0.020 square metres, but values range from 0.004 to 0.27 square metres across aspect angles \u2014 a factor of about 70 at one frequency. In flight at 24 GHz a Phantom 3 measured around minus 20 dBsm.\"}},{\"@type\":\"Question\",\"name\":\"Do drones have a smaller radar cross-section than birds?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Generally no. In the only study to measure both in flight with the same calibrated radars, a DJI Phantom 3 at minus 20 dBsm returned more than a Harris Hawk at minus 22 and far more than a Northern Hawk Owl at minus 30. Only the largest bird tested, a Tawny Eagle, out-returned the drone.\"}},{\"@type\":\"Question\",\"name\":\"Why is it hard to tell a drone from a bird on radar?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Because their radar cross-section distributions overlap almost completely. A Phantom 3 spans minus 29.5 to minus 12 dBsm between the 10th and 90th percentiles; an Indian Eagle Owl spans minus 30 to minus 12.5. Both fly below 30 metres per second. Cross-section and speed cannot separate them, so classification depends on micro-Doppler.\"}},{\"@type\":\"Question\",\"name\":\"What is micro-Doppler and how does it identify drones?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Spinning rotors modulate the radar return into sidebands and into evenly spaced spectrogram stripes called HERM lines. A drone rotor turns at roughly 100 hertz while a bird flaps at 4 to 6 hertz, so the two are easily distinguished in principle. HERM line spacing equals rotation rate times blade count and is independent of radar frequency.\"}},{\"@type\":\"Question\",\"name\":\"Why does a long-range air defence radar miss a low-flying drone?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Geometry, not sensitivity. A published analysis of an L-band air-surveillance radar with a 470 km instrumented range found that with the beam tilted 2.5 degrees up, the beam axis intersects 60 metres altitude at just 690 metres range. The beam passes over low-flying targets, and no signal processing can fix that.\"}},{\"@type\":\"Question\",\"name\":\"Why do counter-drone systems use jammers instead of radar?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Radio-frequency detection listens for the drone\u2019s control link, which is cheaper and simpler than fighting the radar physics. A 2022 US Department of Transportation audit found radar and radio frequency were the two most common detection methods at airports, though it also found airport spectrum congestion made detection difficult or impossible in places.\"}},{\"@type\":\"Question\",\"name\":\"Can fibre-optic drones be jammed or detected by radio?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"No. A drone flown on a spooled glass fibre, a technique that spread rapidly after appearing in the Kursk region in August 2024, has no radio control link. There is nothing to jam and nothing for a radio-frequency sensor to hear, which pushes the detection problem back onto radar, optical and acoustic sensors.\"}}]}<\/script><div style=\"background:#f0f4ff;border-left:4px solid #5C91FF;padding:16px 20px;margin:32px 0 8px\"><p style=\"margin:0 0 8px;font-weight:600;color:#333\">Related Posts<\/p><p style=\"margin:4px 0\"><a href=\"https:\/\/migflug.com\/afterburner\/berlin-brandenburg-ber-drone-shutdown-september-2026\/\">Berlin Brandenburg Shuts Down After a Drone Sighting<\/a><\/p><p style=\"margin:4px 0\"><a href=\"https:\/\/migflug.com\/afterburner\/how-does-radar-work-pulse-doppler-range-bearing-explained\/\">How Does Radar Work? Pulse, Doppler, Range and Bearing<\/a><\/p><p style=\"margin:4px 0\"><a href=\"https:\/\/migflug.com\/afterburner\/radar-horizon-why-flying-under-the-radar-is-literal\/\">The Radar Horizon: Why Flying Under the Radar Is Literal<\/a><\/p><p style=\"margin:4px 0\"><a href=\"https:\/\/migflug.com\/afterburner\/air-defence-interceptor-cost-asymmetry-magazine-depth\/\">The Cost Asymmetry Problem in Air Defence<\/a><\/p><\/div>\r\n","protected":false},"excerpt":{"rendered":"<p>Share this story Every time a drone shuts an airport, the same explanation appears within hours: the things are simply too small for radar to see. It is a tidy story. It is also wrong, and the measurement literature has been saying so for a decade. A DJI Phantom 3 and a pigeon were never [&hellip;]<\/p>\n","protected":false},"author":23,"featured_media":27289084,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"editor_notices":[],"footnotes":""},"categories":[665,664],"tags":[],"class_list":["post-27289766","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-aviation-world","category-military-aviation"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Why Radar Cannot Detect Small Drones | MiGFlug<\/title>\n<meta name=\"description\" content=\"A DJI Phantom returns a stronger radar echo than a pigeon. So why can radar not detect small drones? 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