The invention discloses a tracking measurement set partitioning method for multiple extended targets based on density analysis and spectrum clustering. The method is mainly used for solving the problems that in noisy environments, the number of the multiple extended targets is unknown, a changing measurement set is difficult to partition and the calculating cost is high. The method comprises the steps of constructing a density distribution function for the measurement set by adopting a Gaussian kernel, then, selecting a density threshold according to a density histogram technology, filtering noise wave measurements out of the measurement set, constructing a noise wave measurement data set removed similarity matrix by introducing an affinity propagation technology, finally, carrying out Laplace spectrum transform on the similarity matrix, and clustering by adopting a K-mean algorithm. The method has the advantages that the measurement set of the multiple extended targets can be accurately partitioned, and the calculating cost is reduced, so that the tracking performance for the multiple extended targets is improved, and the design requirements of actual engineering systems are met.