As the Gaussian radial basis function（RBF） is based on the Euclidean distance of two spectral vectors

it is sensitive to spectral curve variations resulted from radiation intensity variation.When the spectral curves of same materials are different

the detection performance of the RBF based OCSVM objective detector will degradate.In order to solve this problem

a nonpositive definite kernel

named as the spectral Angel Cosine Kernel Measure（SACKM）

is proposed based on the spectral curves similarity description

and was applied to object detection based on an indefinite OCSVM method in hyperspectral imagery.Finally

the experiments were carried out with two hyperspectral images

which are used to validate the proposed method.