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линейная и нелинейная частотная модуляция РЛС,P4 code
milstar: линейная частотная модуляция РЛС 28LFM Phase and Frequency Characteristics p 28 https://www.its.bldrdoc.gov/media/31078/DavisRadar_waveforms.pdf ---------------- 5.4.1. Основные характеристики зондирующих сигналов (ЗС). Излучаемый активной РЛС сигнал играет роль инструмента исследования пространства радиолокационного наблюдения и называется зондирующим (ЗС). Известны две наиболее общие формы записи радиосигнала: вещественная и комплексная. При первой форме ЗС имеет вид Sз(t) = UmU(t)cos[2pf0t + j(t)], (1) где: Um – амплитуда излучаемых колебаний; f0 – несущая частота СВЧ колебаний; U(t) – закон амплитудной модуляции (огибающая сигнала); j(t) – закон фазовой модуляции ЗС. Комплексная форма записи ЗС имеет вид (2) где - комплексный закон модуляции ЗС (комплексная огибающая сигнала). Очевидно, что вещественная форма записи ЗС совпадает с действительной частью ее комплексной формы. Для обнаружения целей на малых и предельно малых высотах (менее 1 километра) целесообразно использовать непрерывные ЗС. Как и в случае с одиночными РИ, используемые непрерывные сигналы могут быть немодулированными (НМ) или линейно частотно модулированными . Радиоимпульс с линейной частотной модуляцией (ЛЧМ) является сложным сигналом, база которого больше 1. ЛЧМ радиоимпульс (рис. 1) представляет собой сигнал, у которого в течение длительности импульса tи частота изменяется по линейному закону , (1) где Dfд – девиация частоты. http://zrv.ivo.unn.ru/pages/vtp/5/5-4-radiolokatsionnye-signaly.htm 5.4.6. Импульсные последовательности для связи с ЗУР Для сопровождения ЗУР используются ограниченные во времени последовательности импульсов, которые принято называть «пачками» запросных импульсов, когерентность которых при обработке не учитывается. Возможность использования некогерентных , т.е. не накапливаемых на радиочастоте сигналов, в линии ЗУР - РЛС обусловлена использованием в этой линии метода активной локации с активным ответом. За счет наличия на борту ЗУР передатчика, существенно возрастает мощность сигнала на входе РПрУ РЛС, что и позволяет отказаться от когерентных сигналов. Другим вариантом импульсной последовательности, используемой при работе с ЗУР, является частотно-модулированная последовательность. Она используется для обмена цифровой информацией между ЗУР и РЛС и по существу является не радиолокационным, а связным сигналом. ------------------------ Sandia Lab https://prod-ng.sandia.gov/techlib-noauth/access-control.cgi/2006/065856.pdf •Nonlinear-FM (NLFM) waveforms offer substantial advantages over their Linear-FM (LFM) counterparts. •Generally any practical range sidelobe filtering that can be accomplished with window functions, can also be accomplished by selecting a corresponding NLFM waveform. Matched filter output results will be indistinguishable, except for an increase in SNR using the NLFM waveform. •The design procedure for a NLFM waveform is straight-forward and presented herein. •Hardware architectures for generating suitable NLFM waveforms are also straight-forward, with several options presented herein.
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milstar: Phase-coded radar signals offer a remarkable flavour of diversity that simply depends on the change of the code of the modulation sequence. Such signals are easily generated compared to other diverse radar signals that require changing the carrier frequency. Frequency hopping signals may be considered as diverse code signals, in which its pattern of changing codes is optimized for diversity to avoid jamming, rather than to enhance the range resolution of radar. For a radar that uses a pseudorandom waveform, a comprehensive search of possible waveforms could be attempted. The choice of waveform may be reduced upon many rules, such as search of maximal-length sequences that do not include binary codes of all ‘1s or all ‘0s, which definitely do not accomplish the required resolution. Several codes are satisfactorily close that only one of a set might need to be tried. However, the number of combinations is still big, and extensive search of high time-bandwidth codes could not be practical using available computers. Nevertheless, regarding the current improvement in computer speeds, the power to do this seems to be achievable. For example, if a correlator can correlate a waveform with 1 ms integration length in real time, it could search 10,000 waveforms in only 10 s. Therefore, if all the possible low probabilities of exploitation techniques were employed as efficiently as possible, it becomes so difficult to exploit the transmitted signal within tactical timescales. A great deal of research is being carried on to investigate waveform that designed and the related signal processing for the high-resolution pulse Doppler imaging, both in radar and in sonar https://www.intechopen.com/books/topics-in-radar-signal-processing/adaptive-coding-modulation-and-filtering-of-radar-signals
milstar: The uncertainty association of Fourier transformation states the primary limitation on the ability of any individual waveform to simultaneously resolve two or more targets closely spaced in both time delay and Doppler shift [13]. Transmitting successive signals of adequately diverse waveforms and processing them properly could make it possible to resolve those targets and generate a high-resolution delay-Doppler image. It is somehow similar to the situation of generating a high-resolution optical image from several low-resolution optical images with somehow different imaging apertures. A selection of optimal sets of coded waveforms and designing associated processing algorithms has already been considered [13], for example, in order to generate pulse-echo delay-Doppler images of a substantially higher resolution than that is possible using a single waveform with comparable time-bandwidth product. In an adaptive diverse system, the instantaneous waveform is selected to improve the performance according to changes in clutter and noise variations [8].
milstar: Sensors2021, 21, 449 16 of 18 Figure 13. The effects of different networks on the PSR of the proposed approach. 6. Conclusions Accurate identification of the modulation type of the radar signals plays a prominent part in modern electronic countermeasures. In this paper, the ASVR algorithm with good antinoise capability and strong adaptability is proposed for the first time. Then, deep re-sidual learning is combined with ASVR to identify various radar signals. This method can identify eight types of radar signals (including LFM, SFM, EQFM, FSK, 4FSK, BPSK, Frank code and CW signals) effectively under low SNRs Modulation Recognition of Radar Signals Based on Adaptive Singular Value Reconstruction and Deep Residual Learning https://www.mdpi.com/1424-8220/21/2/449
milstar: https://www.ijariit.com/manuscripts/v3i6/V3I6-1298.pdf Phase Coded Radar Signals – Frank Code & P4 Codes
milstar: Modern radar systems face a variety of threats in electronic support system, radar warning receivers, and electronic attack system. In order to survive, the low probability of interception (LPI) signals is employed by modern radar system. Those LPI signals are typically pulse compression continuous signals, which are difficult to intercept by the electronic intelligence (ELINT) systems. Polyphase codes radar signal (Frank, P1, P2, P3, and P4 codes), which derived from step frequency modulated signal and linear frequency modulated signal, is the most frequently used LPI signal because of its easy digital implementation, its versatility, and its high range resolution and Doppler tolerance [1–6]. In the past two decades, the detection of polyphase codes radar signals has attracted much attention [7–13]. The polyphase codes radar signals exhibit the characteristic of multiple ridges parallel in the time-frequency distribution. According to this characteristic, a variety of methods is proposed for detecting the polyphase codes radar signals. https://www.hindawi.com/journals/mpe/2016/1382960/
milstar: https://www.keysight.com/upload/cmc_upload/All/WS6_Monday_15.15_John_Hansen.pdf © 2012 Agilent Technologies Agilent in Aerospace & DefenseMeasurementTechniquesforRadarandElectronicWarfareApplications
milstar: nvestigates techniques for using low probability of intercept (LPI) modulation techniques for forming synthetic aperture radar (SAR) imagery. This analysis considers a specific waveform type based upon Frank codes in providing for the LPI capability via phase shift keying (PSK) modulation. A correlation receiver that is matched to the transmitted waveform is utilized to generate a set of SAR data. This analysis demonstrates the ability to form SAR images based upon simulated radar measurements collected by a notional radar sensor that has ability to transmit and receive Frank-coded waveforms and to form SAR images based upon the results of a correlation receiver. Spotlight-mode SAR images are generated using the Frank-coded waveforms and their properties are analyzed and discussed. https://www.spiedigitallibrary.org/conference-proceedings-of-spie/9093/1/Phenomenology-of-low-probability-of-intercept-synthetic-aperture-radar-via/10.1117/12.2048638.short?SSO=1 https://core.ac.uk/download/36740714.pdf This paper has examined methods for using Frank-coded transmission waveforms for forming spotlight-modeSAR images. Simulations are developed based upon a matched correlation receiver corresponding to the trans-mitted Frank-modulated waveforms. This analysis demonstrates the ability to form SAR images via Frank-codedtransmission and receiver processing, and that good reconstructions of the image scene can be obtained whileusing such a set of LPI waveforms.
milstar: For instance, a well-known Frank code [1] is derived as the samples at Nyquist rate from a stepped linear frequency modulated waveform. A Frank code compression filter is computationally efficient but its peak to maximum range time-sidelobe ratio deteriorates if the signal is band-limited in the preceding receiver stages. Moreover, the Frank waveform is not tolerant to Doppler shifts which cause considerable distortions ofthe compressed main lobe and a significant loss of signal energy. As an attempt to alleviate the drawbacks of Frankcoding a class of polyphase codes was proposed [2] known as P1-P4 codes. Codes P1 and P2 of this class are tolerant to receiver bandwidth limitations. However, they are based on a stepped approximation to a linear chirp just as the Frank code and share with it the same degree of main lobe distortions and an unacceptable loss of signal energy if a significant Doppler shift is present in the signal. Codes P3 and P4 on the other hand were derived as the samples from a linear frequency modulated (LFM) signal and inherited its tolerance to Doppler shifts. Themaximum of the compressed signal is shifted along the time axis with the Doppler shift as is the case with anLFM signal (which is due to the same causes) but thecompressed waveform is distorted only slightly and there is no significant loss of signal power. In addition, a P4 code is tolerant to receiver bandwidth limitations.Therefore, P4 codes were selected for the researched radar along with some codes based on nonlinear frequency modulation. http://www.wseas.us/e-library/conferences/2005prague/papers/493-118.pdf
milstar: After simulation we find that use of polyphase code in small and medium range and use NLFM and weighted LFM for long range http://www.wseas.us/e-library/conferences/2005prague/papers/493-118.pdf
milstar: FOREWORD Often, especially for power-starved radar systems, the radar designer strives to extract every bit of performance that he is able to coax from his system. A single dB of additional Signal-to-Noise Ratio (SNR) gained elsewhere is equivalent to a 25% increase in transmitter power. Alternatively, a single dB of additional SNR can have dramatic effects in reducing false alarm rates in target detection applications. Consequently we examine herein choosing and creating Nonlinear FM radar waveforms with characteristics that can avoid the typical 1-2 dB of SNR degradation associated with sidelobe filtering that is often required with Linear FM waveforms. Sandia Lab https://prod-ng.sandia.gov/techlib-noauth/access-control.cgi/2006/065856.pdf s fairly readily generated by a variety of technologies, and is easily processed by a variety of techniques that ultimately implement a Matched Filter, or nearly so. However, since a LFM chirp waveform has nearly a rectangular PSD, its autocorrelation function exhibits a sinc() function shape, with its attendant problematic sidelobe structure. Reducing the sidelobes of the Matched Filter output (actually increasing the peak to sidelobe ratio) is typically accomplished by linear filtering the output, most often by applying window functions or data tapering. This additional filtering perturbs the Matched Filter result to reduce sidelobes as desired. However, since the cumulative filtering is no longer precisely matched to the signal, it necessarily reduces output SNR as well, typically by 1-2 dB (depending on the filtering or weighting function used).1It is well-known that Non-Linear FM (NLFM) chirp modulation can advantageously shape the PSD such that the autocorrelation function exhibits substantially reduced sidelobes from its LFM counterpart. Consequently, no additional filtering is required and maximum SNR performance is preserved. However precision NLFM chirps are more difficult to design, produce, and process.
milstar: The progress of technology now offers the possibility of addressing the first two points, namely easily producing and processing the NLFM waveform. The advent of high-speed Digital-to-Analog Converters (DACs) and high-speed large-scale Field ProgrammableGate Arrays (FPGAs) currently facilitate generating high-performance precision digital LFM chirp waveforms.2,3 This suggest that more exotic waveforms might now be within the realm of possibilities. o facilitate a comparison, consider first a conventional Linear FM (LFM) chirp with characteristics in figure 1. Note that the frequency ramp is linear, and the spectrum is flat-topped with steep sides, nearly a rectangle. Note also that the Impulse Response (IPR) is expected to be nearly a sinc() function with −13 dB sidelobes. Figure 1. Example LFM chirp with (a) frequency vs. time, (b) magnitude spectrum, and (c) timeautocorrelation function. Now consider the Non-linear FM (NLFM) chirp with characteristics in figure 2. Note here that the frequency ramp is non-linear, with steeper slope at the beginning and at the end of the pulse. The corresponding spectrum is tapered with lower magnitude at its edges. This spectral shaping results in the autocorrelation function exhibiting attenuated sidelobes, limited to less than −35 dB. Furthermore these characteristics are achieved without any SNR-robbing sidelobe filtering or window functions. https://prod-ng.sandia.gov/techlib-noauth/access-control.cgi/2006/065856.pdf
milstar: RF SamplingS-Band Radar Transmitter Reference Design LFM and NFLM https://www.ti.com/lit/ug/tiduc75/tiduc75.pdf
milstar: https://www.radartutorial.eu/druck/Book4.pdf Pulse compression with non-linear FM waveformThe non-linear FM waveform has several distinct advantages.The non-linear FM waveform requires no amplitude weightingfor time-sidelobe suppression since the FM modulation of thewaveform is designed to provide the desired amplitudespectrum, i.e., low sidelobe levels of the compressed pulse canbe achieved without using amplitude weighting.Matched-filter reception and low sidelobes become compatiblein this design. Thus the loss in signal-to-noise ratio associatedwith weighting by the usual mismatching techniques iseliminated.A symmetrical waveform has a frequency that increases (ordecreases) with time during the first half of the pulse anddecreases (or increases) during the last half of the pulse. A nonsymmetrical waveform is obtained by using one half of asymmetrical waveform.The disadvantages of the non-linear FM waveform are•Greater system complexity•The necessity for a separate FM modulation design foreach type of pulse to achieve the required sidelobelevel
milstar: Digital-to-analog converters (DACs) have been widely used since the 1980s in arbitrary function generators (AFGs) and arbitrary waveform generators (AWGs) to produce signals for verification, characterization, and stress/margin testing. However, advances in DAC technologies and techniques enabled them to directly generate highly detailed RF and electronic-warfare (EW) signals or the complex pulse trains used in advanced research, making them very suitable for high-end applications such as quantum computing. https://www.electronicdesign.com/technologies/test-measurement/article/21805033/how-new-dac-technologies-are-changing-signal-generation-for-test High-Speed DACs with Complex Modulators The latest DACs overcome many of the problems with generating complex microwave signals by integrating more functionality into a single chip. Looking at a simplified block diagram of a high-speed 16-bit DAC being used in next-generation AWGs, the design incorporates a digital complex modulator and multi-rate interpolation (Fig. 2). The complex modulator is a digital implementation of a VSG. The NCO acts as the local oscillator providing the carrier signal. The user-defined I and Q baseband signals are digitally streamed into the DAC from an off-chip memory. The output of this modulator is a digital waveform applied to the DAC core. The NCO’s frequency is controlled using a dedicated on-chip register that can be independently programmed, allowing for the carrier frequency to be tuned without recalculating or reloading of the I-Q waveforms. Interpolation in the digital data path is used to generate waveform data, which is supplied to the DAC at lower sample rates to reduce memory requirements. Two independent interpolation blocks are included—a baseband block with selectable factors from 2x to 16x, and a block associated with the double-data-rate (DDR) clocking feature. When DDR is off, data is converted on only one of the clock edges and the interpolation mode is set to x1. When DDR mode is used, data is 2x interpolated and converted on both edges of the clock signal. While in DDR mode, the NCO’s sample rate also doubles. As a result, at the maximum clock frequency of 5 GHz, the NCO and the DAC core are running at a sample rate of 10 Gsamples/s and carrier frequencies up to 5 GHz in the first Nyquist band can be synthesized. With a reconstruction filter at the output of the AWG, analog signals with complex modulation can be directly generated up to nearly 5 GHz. Signals at higher frequencies are also possible using higher-order Nyquist bands. Superheterodyne Upconversion Even with the improved performance and lower noise floor of the latest DACs, there will be cases where the desired frequency is too high to effectively use the higher-order Nyquist bands, and with good dynamic range. In these cases, a superheterodyne upconversion scheme incorporating the NCO and an external mixer is a useful way to extend the AWG’s output frequency coverage. Superheterodyne upconversion is performed in two stages, where the signal is first upconverted to an intermediate frequency (IF) and, after filtering out the undesired spectral components, the IF spectrum is upconverted again to a higher RF band (Fig. 6).
milstar: 5. Conclusions The good performance of the HFM under a large Doppler effect makes it very useful in high speed moving target detection and imaging. Additionally, the application of the wideband HFM waveform also has the potential to improve the bandwidth efficiency in multi-radar systems, for the low RFI between the LFM and HFM waveforms. In this paper, a new pulse compression method has been proposed for the HFM waveforms. The bandwidth of the demodulated echoes was largely reduced through the decurve processing, and then, both the phase matching method and the efficient method combing resampling and FFT were used to obtain the focused HRRP. For the similarity between the decurve and dechirp processing, the HFM waveform was applied to the existing imaging radar systems that are more convenient with no change in the receiving channel. Both one- and two-dimensional radar imaging results have been taken to prove the correctness of the proposed method. Moreover, when the wideband HFM waveform is applied in the ISAR imaging system, the narrowband tracking signals can be transmitted with a much lower rate, for the velocity tracking information is not needed to get focused range profiles. Therefore, we can achieve a higher wideband data rate with the HFM radar system, which is also significant for the ISAR imaging processing. Although we concentrate on the situation for which the target moves with a constant velocity in this paper, the proposed method still works when the target has a constant acceleration. Additionally, the influence of the target’s acceleration can be easily compensated by a bank of filters with different frequency biases [7,19]. https://www.mdpi.com/1424-8220/15/9/23188/html
milstar: Coherent Seeker Guided AntishipMissile Performance AnalysisJAMES J. GENOVAIntegrated EW Simulation BranchTactical Electronic Warfare Division Naval Research Laboratory https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.928.3912&rep=rep1&type=pdf
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