Doppler through-the-wall radar positioning method based on LASSO feature extraction

Abstract

The present invention belongs to the field of object tracking technology, and discloses a Doppler through-the-wall radar positioning method based on LASSO feature extraction. An LASSO frequency estimation algorithm is employed to separate components of echo signals after demodulation and estimate frequency features of interested object components; a positioning tracking algorithm is employed to estimate position information of an object in real time according to the instantaneous frequency of the object and combine an object motion locus so as to achieve tracking of the object. The Doppler through-the-wall radar positioning method based on LASSO feature extraction can effectively improve positioning precision of the object and can solve the problem of 'fuzzy frequency' on the basis of ensuring conciseness (only one emitter and two receivers are needed) and detection timeliness (fast computing speed) of a Doppler through-the-wall radar positioning system so as to achieve tracking positioning of multiple objects at the same time. Besides, the Doppler through-the-wall radar positioning method based on LASSO feature extraction does not need a tedious calculating process such as multi-channel data fusion and the like, is fast in computing speed, and has a wide application prospect in object tracking field of a Doppler through-the-wall radar.

Description

technical field [0001] The invention belongs to the technical field of target tracking, in particular to a Doppler through-wall radar positioning method based on LASSO feature extraction. Background technique [0002] In recent years, the use of Doppler through-the-wall radar to track human targets has been regarded as a powerful tool with broad application prospects in military and civilian fields. Early research results show that in order to locate moving targets more economically, accurate estimation of the target's instantaneous frequencies (Instantaneous Frequencies, IFs) plays an important role. In order to achieve this goal, the most common way is to use time-frequency analysis technology, by extracting the maximum value in the time-frequency plane as the target time-frequency trajectory. However, the time-frequency analysis method has several major defects: First, due to the particularity of the application of through-wall radar, most observers often hope to obtain ...

AI Technical Summary

Problems solved by technology

However, the time-frequency analysis method has several major defects: First, due to the particularity of the application of through-wall radar, most observers often hope to obtain the detection information of the target in real time, so the length of the time window in the signal processing process has strict requirements. Second, when the instantaneous frequencies of different targets are too close to be accurately identified by the time-frequency analysis algorithm, the algorithm's estimation of the target's instantaneous frequency Accuracy will drop significantly

However, the algorithm is also limited by the cross-term interference problem

And as the phase order increases, the computational complexity of the algorithm will increase exponentially, which will cause a lot of computational pressure on the radar processing unit

[0003] To sum up, the problems existing in the existing technology are: when the target instantaneous frequency is similar, the time-frequency analysis algorithm will inevitably encounter the problem of cross-term interference, while the traditional separation algorithm is prone to modal aliasing. This will lead to a decrease in the estimation accuracy of the instantaneous frequency

Algorithms with calculations of higher-order terms add computational complexity, which puts a lot of pressure on the radar's processing unit

Images