Joint estimation method for space–time frequency parameters of frequency-hopping network station in the case of low-quality data

The parameter estimation of frequency-hopping networks is an important research direction in the field of communication electronic countermeasures(CECM). However, in urban scenarios, non-line-of-sight transmission and noise interference are common, leading to data loss in sensor networks during information acquisition, which poses significant challenges for the parameter estimation of frequency-hopping networks. To address the issue of missing observation data, this paper proposes an atomic norm soft thresholding method that combines time–frequency and angle information as joint feature vectors(AST-JFV) to improve the accuracy of parameter estimation under conditions of partial data loss. It achieves high-precision estimation of hopping time, instantaneous frequency, and direction of arrival for frequency-hopping signals. Experimental results show that with 20% data loss and a SNR of 10 dB, the proposed method achieves an accuracy of over 90% in estimating hopping time, an estimation error of less than 0.1 MHz for instantaneous frequency, and an angle estimation error controlled within 0.5°, with a computation time reduction of over 80%.