The present project aims to make an in-depth study of Radar pulsecompression, Phase Coded pulsecompression codes. Pulsecompression is a method which combines the high energy of a longer pulse width with the high resolution of a narrow pulse width. The major aspects that are considered for a pulsecompressiontechnique are signal to sidelobe ratio (SSR) performance. Matched filtering of biphase coded radar signals create unwanted sidelobes which may mask important information. Hence the study of poly phase codes like six phase pulsecompression code is needed and the implementation techniques are carried out since the poly phase codes have low sidelobes and are better Doppler tolerant. The proposed VLSI architecture can efficiently generate Six Phase pulsecompression sequences while improving some of the parameters like area and speed when compared to previous methods.
Digital pulsecompression is the technique to convert short pulse to long pulse because energy content of long pulse with low peak power would be the same with short pulse having high peak power. In this paper pulsecompression is performed by Matched Filter in signal processing environment. At some finite interval of time the high peak amplitude of signal with narrow bandwidth gives the energy of the transmitted pulse from the radar. Matched filter gives the signal to noise ratio at the receiver output. Sidelobe reduces to -63 db. Signal to noise ratio (SNR) improves to 12dB. Non linear frequency modulated (NLFM) pulsecompression is used. They have been claimed to provide a high range resolution, improved SNR, low cost, good interference mitigation and spectrum weighting function. High range side lobe can cause poor performance in both target and weather detection. The results have been validated using experimental data.
Abstract- The main objective in a pulsed radar system design is to improve range resolution and detection performance of radar. PulseCompression is a signal processing technique that utilizes the benefits of high range resolution ability of short duration pulse and large range detection ability of long duration pulse. However, the pulsecompression filter output in the radar receiver results in higher peak side lobe levels which are not acceptable in many systems when weaker targets are encountered. Thus, higher peak sidelobe levels affect the detection performance of the radar. In this paper, focus is given on which frequency modulated pulsecompressiontechnique achieve lower peak side lobe levels.
Here, the perfect PSL level indicates the zero side lobes. Pulsecompression radar waveforms offer several advantages over uncompressed waveforms. In pulsecompressiontechnique within transmit power limitations; range, Doppler resolution and target detection capabilities are greatly improved. A pulsecompression signal modulation involves switching or keying the amplitude, frequency, phase of the carrier in accordance with the information in binary digits. Frequency-modulated pulsecompression techniques involve sweeping the carrier frequency of the transmit waveform in a linear or nonlinear fashion. For easy implementation phase modulated pulsecompressiontechnique is used.
Mudukutore, et al.,  have proposed phase coded pulsecompressiontechnique to describe the signal returns accurately from the distributed weather targets and the procedure involves the improvement of previous works by considering the effect of target reshufﬂing during the propagation time of the pulse, which is important for long duration pulses. This paper compares the performance of various sidelobe suppression filters and inverse filters based on integrated sidelobe level and Doppler sensitivity and retains the accuracy of parameters in pulse Doppler radar and suppress the sidelobes to an acceptable level through suppression filters.
There are reduction techniques developed to reduce the sidelobe levels. Lewis proposed sliding window two- sample subtractor to reduce the sidelobes for the polyphase codes . Weighting in frequency and time domain can generally be applied to reduce the sidelobes , . This sidelobe reduction technique can be analysed twofold: as matched weighting (with weighting window at the transmitter and the receiver) and mismatched weighting, where amplitude weighting is performed only at receiver site. There is wide range of well-known window functions (Hanning, Hamming, and Nuttallwin) implemented in pulsecompressiontechnique. This paper indicates that Oppermann code has an unsuitable sidelobes level and Doppler tolerant to radars applications. Also, this shows that the use of amplitude weighting functions improves properties of code and makes it as an appropriate technique.
almost impossible to have an ideal pulsecompression filter. By comparing the waveforms in Figure 2, it can be found that the waveform predicted by the square-law (top panel) has high similarity to the scattered pressures of 1 and 2-μm bubbles, but it is very bad for the 3 and 4-μm bubbles. This shows that the pulsecompression filter should be designed differently for bubbles with different sizes and predicts that there will be compression loss for the square-law pulsecompression filter.
The main penalty is that 25% of the power is outside the narrow central part of the pulse. However, this is not significant for applications where it is mainly the peak intensity, that is of importance. One such application is multi-photon microscopy . In this technique, two or more photons are absorbed simultaneously by a prepared sample and the resultant fluorescence is used to obtain information regarding the structural composition. One of the most important features of the excitation source is a sufficiently high peak power, whilst retaining a modest average power. The pulsecompression characteristics afforded by the PCFs would therefore significantly enhance the capabilities of existing commercial laser sources for high-resolution multi-photon fluorescence microscopy.
Though fourphase sequences do not have ideal energy efficiency like binary sequences, better sequences are available at larger lengths. The binary Barker sequences do not exist for length greater than 13, but four phase Barker sequences do exist at length 15. The generation of fourphase 15-bit generalized Barker sequence using acoustic surface waves is reported [10,11]. Richard J. Turyn proved that there are no even length Barker sequences of lengths 6, 8, 10, 12, 14 and also that there are no new fourphase Barker sequences of length ≤ 31 . SAW devices are also used to generate fourphase sequences . J. W. Taylor, Jr. generated good quadriphase or fourphase sequences using biphase to quadriphase transformation . The advantages of these sequences are in the spectrum fall-off rate and the relative ease in which it lends itself to digital processing. Comparison with conventional pulse coding, in particular Barker‟s and Turyn‟sbiphase sequences, the autocorrelation function is preserved when converted to fourphase sequences. The Doppler behavior of the quadriphase codes is proved by Taylor and Blinchikoff to be the same as the Doppler behavior of biphase codes. However, Levanon and Freedman has proved that the ambiguity diagram with a nonzero Doppler shift can be significantly different for a quadriphase code than that of the biphase code from which it was derived . The ambiguity diagram of a quadriphase code derivedfrom a Barker code of length 13 has a diagonal ridge more like that of a linear-FM ambiguity function rather thanthethumbtack ambiguity function of the Barker code. But using these methods generation of fourphase sequences at large lengths has not been reported.
As mentioned in Section 4.b, even for transmitted signals that have proper separation performance via ICA algorithms, their doppler-shifted version of them may have different characteristics in general. But in frequency domain, the Doppler effect causes only a circular shift in the frequency samples, which does not change the statistical characteristics of the data. This forces us to apply our ICA estimator in the frequency domain. Therefore, the applied amplitude and phase code to the transmitted signal should be designed in a special manner to form a BPSK or uniformly distributed signal in the frequency domain. In this article a computer search was used to select proper signals for the ICA technique. According to Fig. 5, different random BPSK or uniformly distributed signals are mixed by an array-matrix of some arbitrary directions and then an ICA estimator is applied to this mixture. The signal which has the highest SIR is selected as the frequency samples of the transmitted signal. In the next step, applying an inverse FFT to the samples, the m×L code of the transmitted pulse train is obtained.
1. INTRODUCTION: Image is basically a two Dimensional signal representation in Digital system. Normally Image which we take from the camera is in the analog form. However for further processing, storage and transmission, images should have to be converted in to its digital form. A Digital Image is 2- Dimensional array of pixels. Basically compression of image is different than compression of digital data. We can use Data compression algorithm for Image compression but the result obtain from that process is less than optimal. Different types of images are used in bio medical, remote sensing and in technique of video processing which require compression for transmission and storage. Compression could be achieved by removing some redundant or extra bits from the image.
An example of such an application that could be opti- mised for such as system is the Spatial and Motion Com- pression (SMC) algorithm, a lossless technique, which has also been developed at Warwick. Although lossly tech- niques are frequently used in applications such as DVD, where complete reconstruction is not necessary, there are an increasing number of applications where total reconstruc- tion, and high compression ratios, are necessary. Exam- ples of such are in professional video postproduction, where lossy techniques would introduce errors within the video stream that would be visible to the trained eye, even at the cost of a low compression ratio. Another example is within the medical imagery sector, where it is necessary to com- press thousands of images but imperative to keep the high quality of the image.
was generated using a Cerenkov scheme . This approach is more compact and less alignment sensitive than the tilted pulse-front method, which is advantageous here because a delay line in the pump beam was used to control the time-delay of this terahertz field. The compression terahertz was focused with an off-axis parabolic mirror onto the butterfly antenna from outside the vacuum chamber through a 6 mm thick silicon window, with an effective focal distance of about ∼ 100 mm. In addition to the delay stage in the compression THz generation path, there is a delay stage in the 515 nm beam, before electron generation. Data collection and the control of the delay stages are automated, and the delay stages can be moved together (for exam- ple, to change the time-delay of the compressed pulses with respect to the streaking THz). The distance between the compression interaction and the streaking interac- tion is ∼ 0.49 m. The detector (TemCam-F416, TVIPS GmbH) is located ∼ 0.55 m further after the streaking. A first solenoid lens focuses the beam to a spot size of 3 µ m (rms) in the compression aperture, and a second lens focuses the beam be- tween the streaking aperture and the camera. The lenses are mounted kinematically to allow precise alignment and avoid temporal distortions , and deflection coils are used to fine-tune the electron alignment at the streaking aperture. A 50- µ m- diameter aperture placed ∼ 100 mm before the butterfly resonator is used to improve the transverse beam emittance. The focus of the beam is placed between the butterfly resonator and the camera, resulting in spot sizes of 11 µ m (rms) at the resonator and 23 µ m (rms) at the camera. Beam sizes in the compression and streaking apertures were determined using knife-edge scans. The same electron optical configuration was used regardless of whether compression was applied. The butterfly resonators are laser-machined in 30- µ m-thick aluminum foil. They were designed for a resonance frequency of 0.3 THz, and simulations predict field enhancement by a factor of ∼ 5 in the center of the resonator. Simulations of the mode profile show that even for the 11 µ m spot size at the streaking resonator, the amplitude of the deflection varies by less than 1 % over the electron beam profile. This is confirmed by the excellent agreement between the fit in Figure 4.2 C, which assumes no amplitude variation, and the data of Figure 4.2 B.
chosen to be either 0 or π radian. If the selection of the 0, π phase is made at random, the waveform approximates a noise modulated signal with a thumbtack ambiguity function, the output of the matched ﬁlter will be a spike of width w with an amplitude N times greater than that of the long pulse. The pulsecompression ratio is N = T /w = BT , where B = 1/w. The output waveform extends a distance T to either side of the peak response, or central spike. The portions of the output waveform other than the spike is called the time sidelobes.
The radar signals simulators became an essential requirement for the development and the evaluation of the performance of the radar systems. Many types of the radar signals simulators were implemented using different techniques. Some of them use digital electronics boards and digital electronics cards as help access to real-world signals and instrumentation for test different types of radar systems, but these types of simulators did not has the ability to generate the radar signals in the intermediate frequency (IF) stage. In this paper, the radar signals simulator in video stage and (IF) stage using PC, arbitrary waveform generator card (DA4300) and National Instruments Digital Electronic Field programmable Gate Array (NI-FPGA) board was proposed. In addition of the hardware requirements, LabVEIW program was used with the FPGA board to generate some of the radar signals such as the synchronization signal (SYNC), Antenna Location signals (ACP1, ACP2 (Angle Clock pulse) and NP (North Pulse)), and others, while Microsoft Visual C++ software was used with the (DA4300) card to generate a transmitted signal, target signal, and other signals in (IF) and video stages. The proposed simulator system has the ability to generate the signals for different types of radars; one of these types is the pulsecompression radar. The generation of linear FM pulsecompression radar signals is compared with the MATLAB Simulink results for this type of radar.
Abstract: Multispectral image acquisition devices produce multi-layer images in which each layer contains the pixel values which are non-negative in nature. Compression of these multi spectral image aims to transform the image into more compact form that is convenient for storage, transmission, processing and retrieval. In this paper a band decomposition and discarding approach is proposed with wavelet and correlation coefficients. The resultant spectral image is subjected for spatial binary plane technique based compression algorithm. The approach is operated in lossless mode and compared against traditional JPEG-LS with multiple metrics. Experiments were conducted on several standard multispectral images that are available for research and observed that the proposed method provides an average compression ratio of 7.34 which is 1.73 times more than earlier method
In the proposed methodology initially all the XML documents are compressed using XML SAX parser. The graphical user interface is designed from where user can select their XML or HTML documents that he/she want to compress. The compressed XML and HTML file will be created in the current working directory with name Compressed XML.xml and Compressed HTML.html as per the file that has been selected by the user. Figure 5 shows the screenshot of HTML compressor where Image Acquisition Toolbox.html file is compressed. The original size of file was 69114 bytes. After compression the size of file is 49474 bytes. The total time required for compression is 234 ms. Figure 6 shows the screenshot where extracting frames from video.html is compressed. The original size of the file was 41762 bytes. After compression the size of file is 36645 bytes. The total time required for compression is 140 ms.
The performance of any image compression scheme depends upon its ability to capture characteristic features from the image, such as sharp edges and fine textures, while reducing the number of parameters used for its modeling . Image compression is one of the most important and successful applications of the wavelet transform. The compression techniques can be classified as: lossless methods and lossy methods. The first class is composed of those methods which reconstruct an im-age identical to the original; the second comprises compression methods which lose some image details after their application: the reconstruction is an approximation of the original image . Well known JPEG based on DCT is lossy compression techniques with relatively high compression ratio which is done by exploiting human visual perception. For the lossy compression, some irrelevant data will be thrown away during the compression. The recovered image is only an approximated version of the original image.