A Truncated Matched Filter Method for Interrupted Sampling Repeater Jamming Suppression Based on Jamming Reconstruction

Interrupted sampling repeater jamming (ISRJ) is becoming more widely used in electronic countermeasures (ECM), thanks to the development of digital radio frequency memory (DRFM). Radar electronic counter-countermeasure (ECCM) is much more difficult when the jamming signal is coherent with the emitted signal. Due to the intermittent transmission feature of ISRJ, the energy accumulation of jamming on the matched filter shows a ‘ladder’ characteristic, whereas the real target signal is continuous. As a consequence, the time delay and distribution of the jamming slice can be obtained based on searching the truncated-matched-filter (TMF) matrix. That is composed of pulse compression (PC) results under matched filters with different lengths. Based on the above theory, this paper proposes a truncated matched filter method by the reconstruction of jamming slices to suppress ISRJ of linear frequency modulation (LFM) radars. The numerical simulations indicate the effectiveness of the proposed method and validate the theoretical analysis.

Low Correlation Codes for Sonar Systems

<p>Sonar is a vital technology for the detection of objects in the water. Sonarsystems have been redefined over many decades, but research is still beingconducted into optimal detection methods. Codes, and the filters thatprocess the codes, have been at the forefront of this research. An importantobjective has been the minimization of interference caused by reflections.Matched filters are commonly used in sonar systems. They are equivalent tocorrelation filters, which are bound by the Welch bound. The Welch boundgoverns the minimum peak correlation for points outside of detection.This thesis investigated matched filters and their bounds, and it wasfound that by relaxing the condition for detection, properties beyond theWelch bound could be achieved. By relaxing these conditions, the Welchbound no longer applies, and so a modified Welch bound was developedto accurately investigate the nature of these codes. In this thesis, methodsto generate codes for these new codes were investigated. Generating codesfor a matched filter is a non-convex problem, so gradient based methodswere utilised. Methods to improve correlation and power characteristicswere developed, along with methods for mapping a sequence for use witha digital transmitter having particular limitations. Mis-matched filters wereused to improve signal characteristics that may be lost due to this mapping.The performance of the generated codes was evaluated, and the rela-tionships between input parameters and output properties of the resultingsignal were observed. These performance assessments demonstrate thattradeoffs are required between various properties, and a balance is neededto obtain codes useful for sonar. The optimization was parametrized by anexample set of requirements for sonar. The signals were found to meet the given requirements, and when compared to codes typically used in sonar,the optimized signals were shown to have significantly better correlationproperties. Furthermore, compared to the general bounds for the propertiesof codes, it was found that the new codes had nearly optimal properties,and performed better than equivalent codes bounded by the Welch bound.The performance of codes were also investigated in a water tank toverify their feasibility. There were several additional considerations whichlimit codes that can be tested, and once these are taken into account thetest provided a robust method to verify the design process. Initial testsshowed results that differed from simulations, but after the inclusion ofzero padding before upscaling, the results from empirical testing agreewith simulation.Summarizing the research in this thesis, a new set of codes were devel-oped using a gradient based optimization method. The codes were mappedto a digital transmitter, and the filter adjusted using a mis-matched filter. The optimization was shown to generate near optimal codes which met allthe given sonar system requirements</p>

Low Correlation Codes for Sonar Systems

<p>Sonar is a vital technology for the detection of objects in the water. Sonarsystems have been redefined over many decades, but research is still beingconducted into optimal detection methods. Codes, and the filters thatprocess the codes, have been at the forefront of this research. An importantobjective has been the minimization of interference caused by reflections.Matched filters are commonly used in sonar systems. They are equivalent tocorrelation filters, which are bound by the Welch bound. The Welch boundgoverns the minimum peak correlation for points outside of detection.This thesis investigated matched filters and their bounds, and it wasfound that by relaxing the condition for detection, properties beyond theWelch bound could be achieved. By relaxing these conditions, the Welchbound no longer applies, and so a modified Welch bound was developedto accurately investigate the nature of these codes. In this thesis, methodsto generate codes for these new codes were investigated. Generating codesfor a matched filter is a non-convex problem, so gradient based methodswere utilised. Methods to improve correlation and power characteristicswere developed, along with methods for mapping a sequence for use witha digital transmitter having particular limitations. Mis-matched filters wereused to improve signal characteristics that may be lost due to this mapping.The performance of the generated codes was evaluated, and the rela-tionships between input parameters and output properties of the resultingsignal were observed. These performance assessments demonstrate thattradeoffs are required between various properties, and a balance is neededto obtain codes useful for sonar. The optimization was parametrized by anexample set of requirements for sonar. The signals were found to meet the given requirements, and when compared to codes typically used in sonar,the optimized signals were shown to have significantly better correlationproperties. Furthermore, compared to the general bounds for the propertiesof codes, it was found that the new codes had nearly optimal properties,and performed better than equivalent codes bounded by the Welch bound.The performance of codes were also investigated in a water tank toverify their feasibility. There were several additional considerations whichlimit codes that can be tested, and once these are taken into account thetest provided a robust method to verify the design process. Initial testsshowed results that differed from simulations, but after the inclusion ofzero padding before upscaling, the results from empirical testing agreewith simulation.Summarizing the research in this thesis, a new set of codes were devel-oped using a gradient based optimization method. The codes were mappedto a digital transmitter, and the filter adjusted using a mis-matched filter. The optimization was shown to generate near optimal codes which met allthe given sonar system requirements</p>

Holographic photonic neuron

The promise of artificial intelligence (AI) to process complex datasets has brought about innovative computing paradigms. While recent developments in quantum-photonic computing have reached significant feats, mimicking our brain’s ability to recognize images are poorly integrated in these ventures. Here, I incorporate orbital angular momentum (OAM) states in a classical Vander Lugt optical correlator to create the holographic photonic neuron (HoloPheuron). The HoloPheuron can memorize an array of matched filters in a single phase-hologram, which is derived by linking OAM states with elements in the array. Successful correlation is independent of intensity and yields photons with OAM states of lℏ, which can be used as a transmission protocol or qudits for quantum computing. The unique OAM identifier establishes the HoloPheuron as a fundamental AI device for pattern recognition that can be scaled and integrated with other computing platforms to build-up a neuromorphic quantum-photonic processor that mimics the brain

Understanding matched filters for precision cosmology

Matched filters are routinely used in cosmology in order to detect galaxy clusters from mm observations through their thermal Sunyaev–Zeldovich (tSZ) signature. In addition, they naturally provide an observable, the detection signal-to-noise or significance, which can be used as a mass proxy in number counts analyses of tSZ-selected cluster samples. In this work, we show that this observable is, in general, non-Gaussian, and that it suffers from a positive bias, which we refer to as optimization bias. Both aspects arise from the fact that the signal-to-noise is constructed through an optimization operation on noisy data, and hold even if the cluster signal is modelled perfectly well, no foregrounds are present, and the noise is Gaussian. After reviewing the general mathematical formalism underlying matched filters, we study the statistics of the signal-to-noise with a set Monte Carlo mock observations, finding it to be well-described by a unit-variance Gaussian for signal-to-noise values of 6 and above, and quantify the magnitude of the optimization bias, for which we give an approximate expression that may be used in practice. We also consider the impact of the bias on the cluster number counts of Planck and the Simons Observatory (SO), finding it to be negligible for the former and potentially significant for the latter.

Synthesis of matched filters.

Methods for approximating the impulse response of a matched, physically realizable filter with the minimum required number of functional nodes are in thei focus of the paper. Methods for approximating the pulse characteristics of a matched filter are proposed, namely: approximation by causal physically realizable functions, which are the correlation functions of the pulse characteristics of low-pass filters (LPF) Butterworth; using the Fourier series to describe the complex transmission coefficient of the filter; direct use of the Fourier series to approximate the impulse response of a matched filter. As a result, the number of elements of the matched filter is significantly reduced.

CHIRP FILTER JAMMING IMMUNITY RESEARCH

The pulse compression technique uses a matched filter to extract an echo signal in the radars receiver. A model of a matched filter for a chirp signal was synthesized using the Simulink Tool of the MATLAB software. Pulse jamming and chirp jamming signals were feed to the input of the matched filter. The output signals were measured. The matched filters degree of suppression of these jamming signals was assessed. Conclusions were made about the jamming immunity of a radar operating with a Chirp matched filter.

SIMULATION MODELING OF THE INTERFERENCE IMMUNITY OF THE RADARS OPERATING WITH COMPRESSED SIGNAL

The immunity to the interference of a radar operating with a pulse compression signal is an important feature. The matched filter is one of the elements of the radar, providing resistance to interference. A model of a matched filter to chirp signal has synthesized using the Simulink tool of the Matlab software. Two types of interference signals have fed to the matched filter input, and the output signals are measured. The matched filters degree of suppression against these two interference signals has been assessed. Inferences about the interference immunity of the radars operating with compressed signals have been made.

JAMMINGIMMUNITY RESEARCH OF A RADAR OPERATING WITH CHIRP SIGNAL

Pulse compressed signal enhances the jamming immunity of a radar operating with such a signal. The matched filter is one of the most important elements in the pulse compression technique. A model of a matched filter for a chirp signal was synthesized using the Simulink tool of the Matlab software. Interference signals were feed to the input of the matched filter and output signals were measured. The matched filters degree of suppression of these interference signals was assessed. Conclusions were made about the jamming immunity of radar operating with chirp signal.

JAMMINGIMMUNITYRESEARCH OF A RADAR OPERATING WITH BARKER CODED PHASE MODULATED SIGNAL

The matched filter is one of the most important elements in the pulse compression technique. Pulse compressed signal enhances the interference immunity of a radar operating with such a signal. A model of the matched filter for a Barker coded phase modulated signal was synthesized using the Simulink tool of the Matlab software. Interference signals were feed to the input of the matched filter and output signals were measured. The matched filters degree of suppression of these interference signals was assessed. Conclusions were made about the jamming immunity of radars operating with Barker coded phase modulated signal.