Abstract
An elliptical Hough transform (EHT) algorithm is proposed in the framework of track-before-detect (TBD) for joint detection and tracking of weak exoatmospheric targets. The new approach exploits the fact that when restricted to a two-body problem, the exoatmospheric target often follows an elliptical orbit, and thus the Hough transform integrated with orbital geometry information would have better detection performance. The relationship between the original radar measurements in data space and the elliptical parameters in parameter space is explicitly derived with multiple steps of coordinate transformation. It is found that the data points mapping into the parameter space essentially represent a quartic curve. An EHT-based algorithm is then designed, and orbit planarity is also taken into account to reduce the effect of noise accumulation. The influences of primary and secondary thresholds and the signal-to-noise ratio (SNR) on the detection performance are compared by simulations. Additionally, a real radar tracking dataset from a scientific satellite on 28 May 2017 is used to investigate the efficiency of the method. By adding some imaginary clutter to the raw orbit, the results indicate that it is very effective in detecting the real satellite trajectory in a low signal-to-noise ratio (SNR) environment. The advantage of the new method lies in it can not only simultaneously detect and track weak exoatmospheric targets but also can predict the trajectory by using these available detected parameters.
Highlights
An important issue in the radar tracking community that arouses wide attention is the detection and tracking of weak targets in very low signal-to-noise ratio (SNR)environments [1,2,3,4,5]
It must be noted that the elliptical Hough transform (EHT) we presented differs vastly from those classical ones used in the detection of ellipses in the image processing field, their names are somewhat similar
If an elliptical curve of points does exist in the THISCS, the curve is represented in Hough parameter space as the point of intersection of all of the mapped quartic curves, i.e., in the parameter space, multiple quartic curves will gather at a point, and the parameters at this point are the desirable ones we are searching for
Summary
An important issue in the radar tracking community that arouses wide attention is the detection and tracking of weak (dim) targets in very low signal-to-noise ratio (SNR). The approach we presented is the elliptical Hough transform (EHT) [40]; we extend this algorithm and test it with field data. Since this approach coincides with the theoretical motion model, it is expected that it will have better performance than that of the simple SHT. For the detection of ellipses in an image, the methods commonly used are the five-dimensional parameter method [41,42], randomized Hough transform (RHT) [43,44], and geometric symmetry method [45,46] These approaches cannot be directly applied to exoatmospheric applications. Concluding remarks and recommendations for follow-on studies are provided in the last section
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