| 摘要 |
A minimum-spanning gradient filter used to suppress clutter in a target detection and tracking system. The minimum-spanning gradient filter uses subspace projection clutter suppression techniques, but does not require eigenanalysis. Model frames of data from a sensor array are stored in a memory in which the model frames do not include targets that are being detected. At start-up, a Gram-Schmidt system generates a series of unit vectors that define a clutter subspace where most of the clutter in the model frames will reside. Current frames of data from the sensor array and unit vectors from the Gram-Schmidt system are applied to a subspace projection system that removes the clutter subspace from the current frames of data. Once the original clutter subspace has been generated, a plane smoothing system updates the clutter subspace as new frames of data are added to the model frames. Current frames of data sent to the subspace projection system are centered. Additionally, a standard deviation for the pixel intensities in each frame of data is applied to a standard deviation threshold to prevent pixels that fall below the threshold from being updated in the clutter subspace. A glint threshold detector is provided to eliminate pixels above a predetermined glint threshold so that they do not contribute to the updated clutter subspace.
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