The paper deals with algorithms for recognizing atmospheric formations with various coherence meteorological radars. It shows that the known recognition algorithms differ in the degree of complexity, and in the completeness of the vector of phenomena and meteorological formation (MF) types to be recognized. Besides, no single structural and algorithmic basis that allows unifying the measurement and recognition problems. To solve this problem, we propose to use the parameters of adaptive lattice filters (ALF), obtained at a stage of ALF tuning with the help of radar returns from MFs. The proposed algorithm is tested using an annual cycle of experimental data on the amplitude fluctuations of incoherent 3-cm radiowave signals reflected from different cloud types. The recognition statistical characteristics obtained with known and proposed methods are compared. It is demonstrated that the proposed way is practically not inferior to the known ones in terms of the accuracy of recognition of returns from MF but it is directly realized while measuring the amplitude fluctuations spectrum of the returns, and this favorably distinguishes it from the others. The tests confirmed the proposed algorithm effectiveness. A unified structural and algorithmic basis for practical realization of the ALF-based measurements of MF parameters and for recognition of dangerous meteorological phenomena is proposed. We show that the proposed algorithm and its practical implementation can, with minor changes, be used in coherent and incoherent radars, as well as in meteorological channels of non-meteorological radars.