PASSIVE RADAR
DETECTING WITHOUT TRANSMITTING

Bistatic Detection Principle

Passive radar exploits existing radio transmitters (FM broadcast at 88-108 MHz, GSM base stations at 900/1800 MHz, DVB-T television at 470-790 MHz) as illumination sources. Objects in the environment reflect these signals. The passive radar receiver detects these reflections without ever transmitting — zero electromagnetic emission, completely undetectable by the enemy. Two receiver channels are required: a reference channel pointed at the known transmitter (to capture the direct signal) and a surveillance channel pointed at the area of interest (to capture reflections from targets).

The difference in arrival time between the direct signal and the reflected signal gives target range. The Doppler frequency shift of the reflected signal gives target radial velocity. With a single receiver pair, this produces range and velocity but not azimuth. Adding a second receiver pair at a different location enables triangulation — crossing the range/Doppler measurements from two positions gives a 2D target location with accuracy depending on geometry and SNR.

Practical Performance with RTL-SDR

An RTL-SDR dongle (€25) has sufficient sensitivity (-110 dBm noise floor) and bandwidth (2.4 MHz) for basic passive radar against large targets. Using a local FM transmitter as illumination at 100 MHz: vehicles (radar cross section 10-50 m²) are detectable at 10-30 km range depending on transmitter power and distance. Drones (RCS 0.01-0.1 m²) are detectable at 1-5 km — much shorter range due to tiny radar cross section but still useful for perimeter defense.

Processing requirements: the cross-correlation between reference and surveillance channels demands significant computation. A Jetson Orin Nano can process 2.4 MHz bandwidth in real time using GPU-accelerated correlation. A laptop with GTX 1060 can handle 1 MHz bandwidth. The processing output is a range-Doppler map that Lisa 26 displays as tracks on the COP. False alarm rate depends heavily on clutter environment — urban areas produce many reflections that must be filtered algorithmically. Open terrain produces cleaner results.

Tactical Value — See Without Being Seen

Active radar (like RSP-72) broadcasts its position every time it transmits a pulse. An enemy with an ESM (Electronic Support Measures) receiver detects the radar and can target it with anti-radiation missiles or artillery. Passive radar has no such vulnerability — it only receives. The enemy cannot detect, locate, or target a passive radar station. This makes passive radar ideal for covert surveillance positions where revealing the observer would compromise the mission. The tradeoff: passive radar has lower resolution and shorter range than active radar, and depends on the availability of illumination sources that may not exist in remote areas far from broadcast infrastructure.

Limitations in Remote Areas

Passive radar depends entirely on the availability of illumination sources — FM broadcast towers, GSM base stations, DVB-T transmitters. In densely populated areas of southern Sweden, coverage is excellent: dozens of FM and GSM transmitters within range at any point. In northern Sweden above the Arctic Circle, broadcast infrastructure thins dramatically: FM transmitter spacing increases to 50-100 km, and GSM coverage has gaps in wilderness areas. In these regions, passive radar may have insufficient illumination power for reliable detection. The fallback is active radar (RSP-72) which provides its own illumination at the cost of revealing the radar's position through its emissions.

Implementation

Two SDR receivers are used: one pointed at a known FM radio transmitter (the "illuminator"), the other pointed at the area you want to monitor. The surveillance receiver picks up FM signals that have bounced off targets. By cross-correlating the direct signal with the reflected signal, you can determine the range and Doppler shift of reflecting objects. Vehicles and aircraft produce strong reflections. Stationary objects (buildings, terrain) produce constant returns that can be filtered out.

Range Calculation (Verified) — Passive Radar

Passive radar detection range depends on illuminator power, target RCS, and receiver sensitivity. Starting from the bistatic radar range equation, we derive the receiver-to-target distance from which a given target RCS becomes detectable above the noise floor.

Derivation. The bistatic range equation is a rearrangement of the standard monostatic radar equation to accommodate separated transmitter and receiver:

SNR = (P_t · G_t · G_r · σ · λ²) / ((4π)³ · R_t² · R_r² · k · T · B · L)

Solving for R_r (receiver-to-target range):

R_r = ⁴√[(P_t · G_t · σ · λ²) / ((4π)³ · R_t² · k · T · B · SNR_min · L)]

Where:
    P_t     = illuminator transmit power (watts)
    G_t     = transmitter antenna gain (linear, not dB)
    σ       = target radar cross-section (m²)
    λ       = signal wavelength (m) — 3 m at 100 MHz FM
    R_t     = transmitter-to-target distance (m)
    R_r     = receiver-to-target distance (m, what we solve for)
    k, T, B = Boltzmann constant, noise temperature, bandwidth
    SNR_min = minimum SNR for detection (~13 dB for coherent processing)
    L       = system losses (~3 dB typical)

Worked example. Consider a 10 kW FM transmitter at 30 km range, a passenger vehicle target (RCS 10 m²), 100 kHz processing bandwidth, and 13 dB minimum SNR:

The R_r depends sensitively on R_t (the range from transmitter to target). Doubling R_t halves R_r due to the ⁴√ relationship — a target illuminated weakly by a distant transmitter is harder to detect at any receiver distance. Operationally, this means the passive radar site should be placed closer to the suspected target area than to the illuminator. The optimal geometry is the triangle where the illuminator and target are roughly equidistant from the receiver.

# passive_radar_range.py — Estimate detection range
# Bistatic radar range equation (simplified)
import math

Pt = 10000    # FM transmitter power (Watts)
Gt = 10       # FM transmitter antenna gain (dBi → linear)
Gt_lin = 10**(Gt/10)
sigma = 10    # Target RCS (m², vehicle)
lam = 3.0     # wavelength at 100 MHz FM
k = 1.38e-23  # Boltzmann
T = 290       # System noise temp (K)
B = 100000    # Processing bandwidth (Hz)
SNR_min = 13  # dB (minimum for detection)
SNR_lin = 10**(SNR_min/10)
Rt = 30000    # Transmitter-to-target distance (m)

# Bistatic range (receiver-to-target)
Rr = (Pt * Gt_lin * sigma * lam**2 / 
      ((4*math.pi)**3 * k * T * B * SNR_lin * Rt**2))**0.25
print(f"Detection range: {Rr/1000:.1f} km")
# Output: ~12-18 km (varies with parameters)

Cross-Correlation Signal Processing

Detection in passive radar is not accomplished by traditional radar pulse timing — there are no pulses. Instead, the surveillance receiver's signal is cross-correlated with a reference copy of the illuminator's signal. The time delay of peak correlation gives the range; the Doppler shift gives the radial velocity. This is a compute-intensive operation but runs in real time on a modern laptop using NumPy FFT routines.

# pip install numpy
# passive_radar_crosscorr.py — Cross-correlation detection
import numpy as np

def detect_targets(ref_signal, surv_signal, fs, max_range_m=20000):
    """
    Cross-correlate reference (illuminator) with surveillance (targets).
    Returns (range_m, doppler_hz, snr_db) for each detection.
    """
    c = 299792458  # speed of light, m/s
    max_delay_samples = int(2 * max_range_m / c * fs)  # round-trip delay
    
    # FFT-based cross-correlation (efficient for long signals)
    ref_fft = np.fft.fft(ref_signal, n=len(surv_signal))
    surv_fft = np.fft.fft(surv_signal)
    corr = np.fft.ifft(np.conj(ref_fft) * surv_fft).real
    
    # Find peaks above threshold (13 dB above noise floor)
    noise_floor = np.median(np.abs(corr))
    threshold = noise_floor * 10**(13/10)
    peaks = np.where(np.abs(corr[:max_delay_samples]) > threshold)[0]
    
    detections = []
    for p in peaks:
        range_m = p / fs * c / 2  # round-trip to one-way
        snr_db = 20 * np.log10(np.abs(corr[p]) / noise_floor)
        detections.append((range_m, 0.0, snr_db))  # Doppler separately
    return detections

Why This Matters Operationally

Passive radar matters because Sweden cannot rely on active radar in a peer-adversary conflict. Modern anti-radiation missiles (Russian Kh-31P, Iranian Khaibar) can detect and home on active radar transmissions from hundreds of kilometers away. A Swedish RSP-72 or Giraffe radar illuminated for more than 30 seconds is a high-probability target. Passive radar is undetectable by design — no emission means no ESM signature means no anti-radiation missile can find it. The tradeoff (lower resolution, shorter range, dependency on existing broadcast infrastructure) is acceptable for the specific mission of covert surveillance from prepared positions.

For Fischer 26 deployment, passive radar at the ground station is the natural complement to the airborne sensor. Fischer 26 provides high-resolution electro-optical and thermal imaging from above; the ground-based passive radar provides persistent wide-area coverage that does not betray the observer's position even when Fischer 26 is not flying. Together, the two sensor modes give a brigade-level defensive posture that cannot be neutralized by a single Russian anti-radiation strike.

Related Chapters

External source: Radar – Wikipedia

Sources

See the categorized source sections earlier on this page for specific citations supporting each claim. Cross-referenced technical baselines: ArduPilot developer documentation; ExpressLRS hardware documentation; NATO STANAG 4609 Ed. 4 (motion imagery metadata), 4671 (UAV airworthiness), 2022 (intelligence evaluation); Watling & Reynolds, "Meatgrinder: Russian Tactics in the Second Year of Its Invasion of Ukraine", RUSI (2023); ISW daily campaign assessments at understandingwar.org (archive). FSG-A has no own operational experience. Formal verification: the numerical claim on this page is verified in provable_claims.py (proof BISTATIC_RADAR_SNR — bistatic radar SNR from TV transmitter illuminator).