用于频谱评估和预测的雷达工具

A. Martone, K. Sherbondy, K. Gallagher, J. Kovarskiy, R. Narayanan
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引用次数: 4

摘要

本文介绍了一种动态电磁环境下雷达频谱接入的评估与预测技术。该技术扩展了现有的频谱感知、多目标优化(SSMO)框架,用于联合优化雷达的信噪比(SINR)和距离分辨率。拟议的框架在一个空间部门收集训练信息,而雷达在另一个空间部门工作。训练信息用于形成SINR和射频(RF)发射器活动的统计估计。预测SSMO (pSSMO)技术然后在雷达操作期间使用训练信息来避免与其他射频发射器发生碰撞。利用所提出的技术对合成的和实测的GSM通信波形数据进行了处理,结果表明仿真数据集和实测数据集具有相似的性能,从而验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Radar tools for spectrum assessment and prediction
In this paper we introduce an assessment and prediction technique for radar spectrum access in a dynamic electromagnetic environment. The proposed technique expands upon the existing spectrum sensing, multi-objective optimization (SSMO) framework for the joint optimization of the radar's signal to interference plus noise ratio (SINR) and range resolution. The proposed framework gathers training information in one spatial sector while the radar operates in another sector. The training information is used to form statistical estimates of the SINR and radio-frequency (RF) emitter activity. The predictive SSMO (pSSMO) technique then uses the training information during radar operation to avoid collisions with other RF emitters. Synthetic and measured Global System for Mobile (GSM) communication waveform data are processed by the proposed technique and the results indicate similar performance between the simulated and measured dataset, thereby validating the results.
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