Optimal Estimation

Knowledge graph centered on Optimal Estimation with 68 nodes and 140 connections. Top connected: evapotranspiration, Precipitation Variability, Elevation Range, Gunnison, Temperature inversion.

Method synopsis

Iterative inversion technique for retrieving atmospheric parameters from contaminated radar measurements using a priori constraints and forward modeling. Accounts for measurement uncertainties and crosstalk effects through covariance matrices.

Synthesized from method descriptions across 2 papers using this protocol.

Procedure from a recent peer-reviewed implementation

Steps below were extracted from the most recent peer-reviewed implementation of this protocol in the corpus — Impact of Crosstalk on Reflectivity and Doppler Measurements for the WIVERN Polarization Diversity Doppler Radar (2023), IEEE Transactions on Geoscience and Remote Sensing. Implementations in other papers (listed below) may differ.

1. Apply optimal estimation retrieval
   Implement iterative OE algorithm to retrieve copolar reflectivity (Zco) and LDR from contaminated measurements. Use temperature-dependent a priori constraints: LDR = -20 dB (T < -3°C), -16 dB (-3° ≤ T ≤ 3°), -25 dB (T > 3°). Apply convergence criteria and noise thresholds.
   Quantities: Maximum 50 iterations per retrieval; convergence parameter Ci < 1; SNR thresholds of 3 dB (surface) and 12 dB (atmosphere)Duration: Iterative process until convergenceConditions: Applied to all range gates with detectable signal
   Equipment: Optimal estimation algorithm, Forward model incorporating crosstalk

Typical Equipment

• Optimal estimation algorithm
• Forward model incorporating crosstalk

Output Measurements

• copolar reflectivity
• linear depolarization ratio
• retrieval uncertainties

Papers Using This Protocol (2)

Places Where Used