scholarly journals Coherent integration and detection algorithm for hypersonic target based on modified pulse compression and Keystone transform

2021 ◽  
Author(s):  
Wenchao Yu ◽  
Xingyu Lu ◽  
Weimin Su ◽  
Hong Gu ◽  
Jianchao Yang
Keyword(s):  
Pulse Compression ◽  
Detection Algorithm ◽  
Keystone Transform ◽  
Coherent Integration

scholarly journals Algorithms for Doppler Spectral Density Data Quality Control and Merging for the Ka-Band Solid-State Transmitter Cloud Radar

2019 ◽  
Vol 11 (2) ◽  
pp. 209 ◽  
Author(s):  
Liping Liu ◽  
Jiafeng Zheng
Keyword(s):  
Spectral Density ◽  
Data Quality ◽  
Pulse Compression ◽  
Doppler Velocity ◽  
Data Quality Control ◽  
Density Data ◽  
Cloud Radar ◽  
Coherent Integration ◽  
Reflectivity Spectra ◽  
The Individual

The Chinese Ka-band solid-state transmitter cloud radar (CR) can operate in three different work modes with different pulse widths and coherent integration and non-coherent integration numbers to meet the requirement for long-term cloud measurements. The CR was used to observe cloud and precipitation data in southern China in 2016. In order to resolve the data quality problems caused by coherent integration and pulse compression, which are used to detect weak cloud in the cloud radar, this study focuses on analyzing the consistencies of reflectivity spectra using the three modes and the influence of coherent integration and pulse compression, developing an algorithm for Doppler spectral density data quality control (QC) and merging based on multiple-mode observation data. After dealiasing Doppler velocity and artefact removal, the three types of Doppler spectral density data were merged. Then, Doppler moments such as reflectivity, radial velocity, and spectral width were recalculated from the merged reflectivity spectra. Performance of the merging algorithm was evaluated. Three conclusions were drawn. Firstly, four rounds of coherent integration with a pulse repetition frequency (PRF) of 8333 Hz underestimated the reflectivity spectra for Doppler velocities exceeding 2 m·s−1, causing a large negative bias in the reflectivity and radial velocity when large drops were present. In contrast, two rounds of coherent integration affected the reflectivity spectra to a lesser extent. The reflectivity spectra were underestimated for low signal-to-noise ratios in the low-sensitivity mode. Secondly, pulse compression improved the radar sensitivity and air vertical speed observation, whereas the precipitation mode and coherent integration led to an underestimation of the number concentration of big raindrops and an overestimation of the number concentration of small drops. Thirdly, a comparison of the individual spectra with the merged reflectivity spectra showed that the Doppler moments filled in the gaps in the individual spectra during weak cloud periods, reduced the effects of coherent integration and pulse compression in liquid precipitation, mitigated the aliasing of Doppler velocity, and removed the artefacts, yielding a comprehensive and accurate depiction of most of the clouds and precipitation in the vertical column above the radar. The recalculated moments of the Doppler spectra had better quality than those merged from raw data.

scholarly journals ISAR Autofocus Imaging Algorithm for Maneuvering Targets Based on Phase Retrieval and Keystone Transform

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Hongyin Shi ◽  
Ting Yang ◽  
Yue Liu ◽  
Jingjing Si
Keyword(s):  
Rotational Motion ◽  
Phase Retrieval ◽  
Translational Motion ◽  
Retrieval Algorithm ◽  
Imaging Method ◽  
Keystone Transform ◽  
Maneuvering Targets ◽  
Coherent Integration ◽  
Motion Parameters ◽  
Phase Retrieval Algorithm

In the current scenario of high-range resolution radar and noncooperative target, the rotational motion parameters of the target are unknown and migration through resolution cells (MTRC) is apparent in the obtained inverse synthetic aperture radar (ISAR)images, in both slant-range and cross-range directions. In the case of the high-speed maneuvering target with a small value of rotation, the phase retrieval algorithm can be applied to compensate for the translational motion to form an autofocusing image. However, when the target has a relatively large rotation angle during the coherent integration time, phase retrieval method cannot get an acceptable image for viewing and analysis as the location of the scatterer will not be true due to the Doppler shift imposed by the target’s rotational motion. In this paper, a novel ISAR imaging method for maneuvering targets based on phase retrieval and keystone transform is proposed, which can effectively solve the above problems. First, the keystone transform is used to solve the MTRC effects caused by the rotation component. Next, phase errors caused by the remaining translational motion will be removed by employing phase retrieval algorithm, allowing the scatterers are always kept in their range cells. Finally, the Doppler frequency shifts of scatterers will be time invariant in the phase of the received signal. Furthermore, this approach does not need to estimate the motion parameters of the target, which simplifies the processing steps. The simulated results demonstrate the validity of this method.

scholarly journals Generalized Dechirp-Keystone Transform for Radar High-Speed Maneuvering Target Detection and Localization

2021 ◽  
Vol 13 (17) ◽  
pp. 3367
Author(s):  
Jibin Zheng ◽  
Kangle Zhu ◽  
Zhiyong Niu ◽  
Hongwei Liu ◽  
Qing Huo Liu
Keyword(s):  
Target Detection ◽  
High Speed ◽  
Computational Cost ◽  
Noise Performance ◽  
Maneuvering Target ◽  
Keystone Transform ◽  
Coherent Integration ◽  
Range Function ◽  
Long Time ◽  
Detection And Localization

The multivariate range function of the high-speed maneuvering target induces modulations on both the envelop and phase, i.e., the range cell migration (RCM) and Doppler frequency migration (DFM) which degrade the long-time coherent integration used for detection and localization. To solve this problem, many long-time coherent integration methods have been proposed. Based on mechanisms of typical methods, this paper names two signal processing modes, i.e., processing unification (PU) mode and processing separation (PS) mode, and presents their general forms. Thereafter, based on the principle of the PS mode, a novel long-time coherent integration method, known as the generalized dechirp-keystone transform (GDKT), is proposed for radar high-speed maneuvering target detection and localization. The computational cost, energy integration, peak-to-sidelobe level (PSL), resolution, and anti-noise performance of the GDKT are analyzed and compared with those of the maximum likelihood estimation (MLE) method and keystone transform-dechirp (KTD) method. With mathematical analyses and numerical simulations, we validate two main superiorities of the GDKT, including (1) the statistically optimal anti-noise performance, and (2) the low computational cost. The real radar data is also used to validate the GDKT. It is worthwhile noting that, based on closed analytical formulae of the MLE method, KTD method, and GDKT, several doubts in radar high-speed maneuvering target detection and localization are mathematically interpreted, such as the blind speed sidelobe (BSSL) and the relationship between the PU and PS modes.

Dim Moving Target’s Detection Based on Keystone Transform

2013 ◽  
Vol 303-306 ◽  
pp. 986-990
Author(s):  
Yun Fei Guo ◽  
Ting Ting Feng ◽  
Xin Liu ◽  
Kong Shuai Fan
Keyword(s):  
Detection System ◽  
Integration Time ◽  
Integration Algorithm ◽  
Keystone Transform ◽  
System A ◽  
Coherent Integration ◽  
Integration Period ◽  
Long Time ◽  
Integration Effect ◽  
Range Migration

For the problem of weak target’s detection under lower signal noise ratio in radar detection system, a key technique is to enhance target echo energy by long time coherent integration. During the integration period, the target may migrate across radar range cells with integration time increasing. Direct coherent integration will lead to echo energy spread in range cells and deteriorate integration effect. A coherent integration algorithm based on a modified keystone transform is proposed in this paper. It can correct range migration caused by the radial velocity of the moving target before coherent integration. Simulation result shows that the proposed algorithm can correct range migration efficiently and improve coherent integration capability.

Sign in / Sign up

Export Citation Format

Share Document