mytec
defa3ad440
Major refactoring of RFCP backend: - Modular propagation models (8 models) - SharedMemoryManager for terrain data - ProcessPoolExecutor parallel processing - WebSocket progress streaming - Building filtering pipeline (351k → 15k) - 82 unit tests Performance: Standard preset 38s → 5s (7.6x speedup) Known issue: Detailed preset timeout (fix in 3.1.0)
75 lines
2.0 KiB
Python
75 lines
2.0 KiB
Python
"""
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ITU-R P.1546 model for point-to-area predictions.
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Valid for:
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- Frequency: 30-3000 MHz
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- Distance: 1-1000 km
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- Time percentages: 1%, 10%, 50%
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Best for: VHF/UHF broadcasting and land mobile services.
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Reference: ITU-R P.1546-6 (2019)
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"""
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import math
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from app.propagation.base import PropagationModel, PropagationInput, PropagationOutput
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class ITUR_P1546Model(PropagationModel):
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"""
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Simplified P.1546 implementation.
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Full implementation would include terrain clearance angle,
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mixed path (land/sea), and time variability.
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"""
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@property
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def name(self) -> str:
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return "ITU-R-P.1546"
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@property
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def frequency_range(self) -> tuple:
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return (30, 3000)
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@property
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def distance_range(self) -> tuple:
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return (1000, 1000000) # 1-1000 km
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def calculate(self, input: PropagationInput) -> PropagationOutput:
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f = input.frequency_mhz
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d = max(input.distance_m / 1000, 1.0) # km
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h1 = max(input.tx_height_m, 1.0)
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# Nominal frequency bands
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if f < 100:
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f_nom = 100
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elif f < 600:
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f_nom = 600
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else:
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f_nom = 2000
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# Basic field strength at 1 kW ERP (from curves, simplified regression)
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E_ref = 106.9 - 20 * math.log10(d) # dBuV/m at 1kW
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# Height gain for transmitter
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delta_h1 = 20 * math.log10(h1 / 10) if h1 > 10 else 0
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# Frequency correction
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delta_f = 20 * math.log10(f / f_nom)
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# Convert field strength to path loss
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# L = 139.3 - E + 20*log10(f) (for 50 Ohm)
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E = E_ref + delta_h1 - delta_f
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L = 139.3 - E + 20 * math.log10(f)
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return PropagationOutput(
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path_loss_db=L,
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model_name=self.name,
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is_los=d < 5,
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breakdown={
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"reference_field": E_ref,
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"height_gain": delta_h1,
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"frequency_correction": delta_f,
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"path_loss": L,
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},
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)
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