Analytic formulation for broadband rough surface and volumetric scattering including matched-filter range resolution

2014 ◽  
Vol 136 (4) ◽  
pp. 2298-2298
Author(s):  
Wei Huang ◽  
Delin Wang ◽  
Purnima Ratilal
Keyword(s):  
Rough Surface ◽  
Matched Filter ◽  
Range Resolution

scholarly journals Performance of Ternary Sequence using Basic Cuckoo Search Algorithm

2019 ◽  
Vol 9 (2) ◽  
pp. 71-75
Keyword(s):  
Matched Filter ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Matched Filtering ◽  
Detection Range ◽  
Range Resolution ◽  
Auto Correlation ◽  
Radar Applications ◽  
Random Codes

Matched filtering is broadly used in various radar applications and communication fields whose output indicates some range sidelobes which may mask some stronger targets. This problem can be overcome by using mismatched filter after the matched filter which increases the performance that is in terms of peak sidelobe ratio. The proposed algorithm is suitable to obtain superior performancein range resolution and detection range simultaneously. The characteristics of chaotic codes such as auto-correlation and cross-correlation are same as random codes. So the input is considered as binary and ternary chaotic sequence which is undergone matched filtering process which is then undergo mismatched filter for further reduction in the sidelobe levels. The design of mismatched filter is adapted with cuckoo search algorithm that uses Lévydistribution. It is observed that the performance of the ternary sequence is significantly improved at the output and this method is extended to various length of ternary sequences.

scholarly journals Implementation of Multi-Objective Grey Wolf Optimizer to Minimize The Sidelobes And Reduce Mainlobe Width

2018 ◽  
Vol 7 (2.20) ◽  
pp. 219
Author(s):  
K Ravi Kumar ◽  
Prof. P. Rajesh Kumar
Keyword(s):  
Frequency Modulation ◽  
Pulse Compression ◽  
Matched Filter ◽  
High Energy ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Compression Technique ◽  
Range Resolution ◽  
Multi Objective ◽  
Small Targets

Range resolution in radar can be achieved by splitting the long pulse of high energy into the high bandwidth of short pulses using pulse compression technique. Frequency modulation (Linear frequency modulation (LFM)) signal is used to improve range resolution. To get better range resolution, frequency step is introduced between a train of LFM pulses known as stepped frequency pulse train (the SFPT). The SFPT suffers from grating lobes when the product of sub-pulse duration and frequency step becomes more than one. The grating lobes and sidelobes present in the vicinity of the mainlobe. It can cause the false alarm detection and hide the small targets. In this work, Multi-Objective Grey Wolf Algorithm (MOGWO) is used to set the parameters of SFPT to mitigate the grating lobes and minimize the sidelobes at the matched filter output. Trade-off solutions between sidelobes versus grating lobes and mainlobe width versus sidelobes are obtained using the Pareto front for different ranges of SFPT parameters.  

Enhanced range resolution: comparison with the matched filter

2017 ◽  
pp. 37-60 ◽  
Author(s):  
Krasin Georgiev Georgiev ◽  
Alessio Balleri Balleri ◽  
Andy Stove Stove ◽  
Marc W. Holderied Holderied
Keyword(s):  
Matched Filter ◽  
Range Resolution

scholarly journals The EISCAT meteor code

2008 ◽  
Vol 26 (8) ◽  
pp. 2303-2309 ◽  
Author(s):  
G. Wannberg ◽  
A. Westman ◽  
J. Kero ◽  
C. Szasz ◽  
A. Pellinen-Wannberg
Keyword(s):  
Matched Filter ◽  
Binary Sequence ◽  
Time Of Flight ◽  
Target Range ◽  
Doppler Velocity ◽  
Range Resolution ◽  
Doppler Shifts ◽  
Low Sidelobe ◽  
Short Time ◽  
Receiver Bandwidth

Abstract. The EISCAT UHF system has the unique capability to determine meteor vector velocities from the head echo Doppler shifts measured at the three sites. Since even meteors spending a very short time in the common volume produce analysable events, the technique lends itself ideally to mapping the orbits of meteors arriving from arbitrary directions over most of the upper hemisphere. A radar mode optimised for this application was developed in 2001/2002. A specially selected low-sidelobe 32-bit pseudo-random binary sequence is used to binary phase shift key (BPSK) the transmitted carrier. The baud-length is 2.4 μs and the receiver bandwidth is 1.6 MHz to accommodate both the resulting modulation bandwidth and the target Doppler shift. Sampling is at 0.6 μs, corresponding to 90-m range resolution. Target range and Doppler velocity are extracted from the raw data in a multi-step matched-filter procedure. For strong (SNR>5) events the Doppler velocity standard deviation is 100–150 m/s. The effective range resolution is about 30 m, allowing very accurate time-of-flight velocity estimates. On average, Doppler and time-of-flight (TOF) velocities agree to within about one part in 103. Two or more targets simultaneously present in the beam can be resolved down to a range separation <300 m as long as their Doppler shifts differ by more than a few km/s.

Polarimetric matched filter for coherent imaging

1988 ◽  
Vol 66 (10) ◽  
pp. 871-877 ◽  
Author(s):  
Alexander B. Kostinski ◽  
Brian D. James ◽  
Wolfgang-M. Boerner
Keyword(s):  
Rough Surface ◽  
San Francisco ◽  
Matched Filter ◽  
San Francisco Bay Area ◽  
Image Contrast ◽  
Coherent Imaging ◽  
Polarimetric Synthetic Aperture Radar ◽  
Bay Area ◽  
Processing Techniques ◽  
Polarization Scattering Matrix

In this paper we focus on image-contrast optimization between two rough-surface classes. Our approach is based strictly on polarimetric filtering, and therefore, no digital image-processing techniques are employed. The approach is tested on a complete polarimetric synthetic aperture radar (POL-SAR) image of the San Francisco Bay area. The data have been taken with the National Aeronautics and Space Administration – Jet Propulsion Laboratory CV-990L-band POL-SAR system, where eight real numbers (complex elements of a 2 × 2 polarization scattering matrix) are associated with each image pixel. Optimal transmitted polarizations (corresponding to maxima or minima of reflected energy) are found for each image pixel, and the results are analyzed statistically via a set of joint two-dimensional histograms. This is done for both of the rough-surface classes. The image response to the "optimal" incident polarization is then simulated digitally by adjusting the receiver polarization according to the modes of the histograms. The corresponding images are computed and displayed with significant image-contrast improvement.

Matched-Filter Loss From Time-Varying Rough-Surface Reflection With a Small Effective Ensonified Area

2018 ◽  
Vol 43 (2) ◽  
pp. 506-522 ◽  
Author(s):  
Douglas A. Abraham ◽  
Stefan M. Murphy ◽  
Paul C. Hines ◽  
Anthony P. Lyons
Keyword(s):  
Rough Surface ◽  
Matched Filter ◽  
Time Varying ◽  
Surface Reflection

Simulation Research on how to Improve the Range Resolution of Pulse Compression Radar Based on Phase Coding

2011 ◽  
Vol 143-144 ◽  
pp. 634-638 ◽  
Author(s):  
Yu Tang
Keyword(s):  
Compression Ratio ◽  
Pulse Compression ◽  
Matched Filter ◽  
Side Lobe ◽  
Radar System ◽  
Radar Signal ◽  
Pulse Modulation ◽  
Range Resolution ◽  
Set Up ◽  
Barker Codes

Phase coded radar signal is one of the pulse-pulse modulation signal in the radar system. Based on the characteristics of matched filtering, we theoretically analyze the basic principle of the phase coded compression radar system. In the Matlab platform, we set up a simulation model which is used for matching filter, when the radar transmitting signal is Barke code signal. The simulation results show that Echo signal can obtain certain pulse compression ratio. By the matched filter, the main lobe amplitude of 13 bits Barker code signal is 22 times the rate of side-lobe. 13 bits Barker codes by the matched filter have the maximum pulse compression ratio.

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