Evaporation duct helps in the over-the-horizon operating of the communication

radar systems

etc. at the microwave frequency band. In addition

it causes abnormal blind areas

too. Therefore

the evaporation duct situation acquisition is the key to seize the mastery of the electromagnetic. However

if the density of the sensor is increased to improve the sensing resolution

the cost is high and the improvement is limited. Compressed sensing (CS) provides the theoretical basis for the awareness of evaporation duct

which is recovered from a small number of low speed measurements. The blind adaptive Karhunen-Loéve transform (BAKLT) pursuit is able to fully exploit the sparsity and reconstruct the time and space situation of the evaporation duct. The analysis and simulation demonstrate that the BAKLT evaporation duct situational awareness accuracy is better than that of the control group using discrete cosine transform. The reconstructed result of the proposed method is able to reach the reconstructed SNR level of 30dB saving 90% of the sampling resources

and provides the compression basis for the full time global evaporation duct situation acquisition.