## 4 Conclusions  
This research introduces a novel radar detection method to overcome the persistent challenge of false alarms and accurate target identification in cluttered environments. The combination of the clutter map constant false alarm rate technique with the Gabor transform in this method is meant to reduce the number of false alarms generated by the  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**No.** & **Titles** & **Methods** & **Advantages** & **Limits** & **References** \\ \hline \multirow{4}{*}{4} & Neural-Network-Based Multitarget Detection & A unified NN model to process the time-domain radar signal for a variety of signal-to-clutter-plus-noise ratios (SCNRs) & \(\bullet\) Robustness in the case of increases in the number of targets. \(\bullet\) Good performance advantage for various clutter “spikiness” conditions in terms of probability of detection and detection threshold sensitivity. & \multirow{4}{*}{[27]} \\  & & & & \\ \cline{1-1}  & & The Improved Constant False & & & \\ \cline{1-1}  & & Alarm Rate Detector Based on & Multiframe integration in heavy-tailed clutter for the radar with high resolution and even smaller grazing angle. & \(\bullet\) Words well with the presence of target-like outliers in the heavy-tailed clutter. & \multirow{4}{*}{[14]} \\ \multirow{4}{*}{5} & \multirow{4}{*}{[5]} & & & \\  & & & & \\  & & Heavy-Tailed Clutter & & & \\  
radar system and to be able to distinguish the target from the false alarms in cluttered environments. We have realized several Monte Carlo simulations in two different scenarios focused on the distance and the number of targets where we used three different clutter models in each scenario to put the targets in difficult conditions. Also, to test the limits of the proposed method, some parameters have been increased in some cases and decreased in others. The proposed method allowed us to reduce the false alarms and detect the targets in the scenarios, compared with the order statistic constant false alarm rate technique that showed several false alarms during the simulations, demonstrating the efficiency and superiority of our method in mitigating clutter interference while maintaining a low false alarm rate. We observed the successful performance of the proposed method even in some cases where the parameters were modified, showing its adaptability. Despite certain limitations, such as computational complexity and parameter sensitivity, our proposed method serves as a solid foundation for further research and improvement. We suggest, for further improvement, choosing another time-frequency technique that can be used to increase the radar resolution. Also, the results of our work lead us to consider other detection methods for complex environments, such as clutter intensity statistics, which can obtain a high probability of detection, or the fluorescent nanodiamonds technique for detection and tracking.  
A.H.M.M.: investigation, data curation, writing--original draft, and writing--review and editing. Y.Z.: conceptualization, supervision, and funding acquisition. C.K.F.M.: writing--review and editing. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the National Natural Science Foundation of China under Grants U20B2040 and 62203359, the Natural Science Basic Research Plan in Shaanxi Province of China under Grant 2022 JQ-654, and the Fundamental Research Funds for the Central Universities under Grant 3102021 ZDHQD10.  
Not applicable.  
The data presented in this study are available on request from the corresponding author due to privacy.  
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The funders had no role in the design of this study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.