The invention relates to a
radar,
inertia and vision fusion navigation method of an
inertia-guided attention mechanism, which comprises the following steps of: acquiring and
processing vision /
inertia /
laser radar navigation data, and performing time / space characteristic
decomposition on double-frame data of an image and a
radar by utilizing a space-time attention separation mechanism so as to extract and obtain inertia-guided motion information characteristics; the method comprises the following steps: generating a key weight through a hidden state of a long short-
term memory network by inertial features through an inertial guidance attention strategy network, carrying out interaction under a multi-
modal attention framework, and generating a binary decision value through a Gumbel-Sigmoid method; and performing selective masking on visual and
laser radar features according to a decision result, fusing the visual and
laser radar features with inertial features, inputting the fused features into an LSTM
pose estimation network, and outputting a high-precision six-degree-of-freedom
pose. According to the method, visual and radar information is selectively extracted, so that robust, energy-saving and interpretable
modal selection and accurate
pose estimation are realized.