Due to its ease of implementation without an additional transmitter, radar communication integrated systems using conventional communication signals have become an effective means for monitoring unmanned aerial vehicles and other aircraft. However, their non-ideal radar signal form causes strong signals to mask weak signals, and clutter suppression is required to detect a target. As the energy of a target signal is extremely low and conventional clutter suppression methods have limited performance, the residual clutter persists after the time-varying clutter is suppressed, resulting in many false alarm points on the processed range–Doppler (RD) map. The two-dimensional distribution of these false alarms on the range–Doppler is very similar to that of the target and difficult to discriminate, which seriously affects target detection and tracking. To reduce false alarm points and improve the performance of target detection, the difference in the spatial–temporal stationarity between a target signal and clutter in a short time is discussed in this paper; a radar false alarm suppression method based on a target’s spatial–temporal stationarity is proposed by using the difference in the stationarity between the target signal and false alarm points in the range, Doppler, energy and azimuth. In this algorithm, to ensure the short-time stationarity of the target, the RD map of the short-time interval sub-frames is obtained by using the sliding matching filtering method and the peak points are extracted. Then, the Mahalanobis distance between the peak points of each sub-frame is used to eliminate the false alarm points. Finally, the false alarm points are further eliminated by target tracking and the real target information to improve the radar target detection performance. The simulation experiments show that this method can eliminate more than 90% of the false alarms points while maintaining the target detection performance. The analysis of actual data obtained from the field experiment indicate that the implementation of this algorithm, which effectively suppresses false alarms, leads to improved target detection outcomes. These enhancements can facilitate the tracking of UAVs and other aircraft.


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    Titel :

    Radar False Alarm Suppression Based on Target Spatial Temporal Stationarity for UAV Detecting


    Beteiligte:
    Chunlin Sun (Autor:in) / Xingpeng Mao (Autor:in) / Zhibo Tang (Autor:in) / Peng Lou (Autor:in)


    Erscheinungsdatum :

    2024




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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