sea clutter

Two Approaches of Detecting Weak Moving Target with Constant Acceleration in Sea Clutter

两种海杂波背景下的微弱匀加速运动目标检测方法

It studies and analyzes the Radar Cross-section, the divisiory method for the clutter units and the scattering characteristics of ground and sea clutter.

研究分析了杂波的雷达散射截面积、杂波网格单元划分方法和地、海杂波的散射特性。

In this paper, details of the experimental equipment and measured method are introduced, and the parameter of the ionosphere condition and ocean state, such as wind direction and ocean current, are derived from HF Doppler spectra of the sea and land clutter.

介绍了获得海洋回波谱的信号处理方法，并由海洋回波Doppler谱计算了电离层状参数和风向、海流等海洋状态参数。

Detecting Weak Signal in Chaotic Sea Clutter Using RBF Neural Network Predictor

基于神经网络预测器的混沌海杂波弱信号检测

Small targets detection in sea clutter by AR double poles analysis

海面小目标检测的AR双极点分析

Small Target Detection Within Sea Clutter Based on Amplitude Standard Deviation

基于幅值标准偏差的海杂波背景下小目标检测

Analysis of simulated sea clutter indicates that sea clutter are chaotic, dissipative and physically realizable system.

最后,利用混沌理论对海杂波进行分析, 得出海杂波接近实际应用环境下的混沌特性.

At last we present a methord for the detection of signals in sea clutter, which is based on the error energy of the BP neural network.

然后采用IPIX雷达海面回波中的水平极化雷达数据对BP神经网络进行训练，结果表明所设计的BP神经网络能够很好的模拟海杂波，单步预测误差较小。

Due to the time-varying beamforming coefficient breaks the correlation of target and sea-clutter in the whole coherent process interval ( CPI), the Bragg peaks will spread after the Doppler processing.

时变的波束形成系数破坏了积累周期中海面动目标和海杂波的相关性，多普勒处理后Bragg峰扩散引起基底抬高。

Then it is proposed to treat the sea clutter as a stationary AR model and establish AR model by estimate their order and parameters.

随后提出将海杂波作为一种平稳的AR模型，通过估计模型的阶数和参数建立AR模型，并据此建立了一种能够准确地模拟海杂波的线性预测检测器。