Ambiguity Function Of Signal Research Articles

On a Closer Look of a Doppler Tolerant Noise Radar Waveform in Surveillance Applications.

The prevalence of Low Probability of Interception (LPI) and Low Probability of Exploitation (LPE) radars in contemporary Electronic Warfare (EW) presents an ongoing challenge to defense mechanisms, compelling constant advances in protective strategies. Noise radars are examples of LPI and LPE systems that gained substantial prominence in the past decade despite exhibiting a common drawback of limited Doppler tolerance. The Advanced Pulse Compression Noise (APCN) waveform is a stochastic radar signal proposed to amalgamate the LPI and LPE attributes of a random waveform with the Doppler tolerance feature inherent to a linear frequency modulation. In the present work, we derive closed-form expressions describing the APCN signal's ambiguity function and spectral containment that allow for a proper analysis of its detection performance and ability to remove range ambiguities as a function of its stochastic parameters. This paper also presents a more detailed address of the LPI/LPE characteristic of APCN signals claimed in previous works. We show that sophisticated Electronic Intelligence (ELINT) systems that employ Time Frequency Analysis (TFA) and image processing methods may intercept APCN and estimate important parameters of APCN waveforms, such as bandwidth, operating frequency, time duration, and pulse repetition interval. We also present a method designed to intercept and exploit the unique characteristics of the APCN waveform. Its performance is evaluated based on the probability of such an ELINT system detecting an APCN radar signal as a function of the Signal-to-Noise Ratio (SNR) in the ELINT system. We evaluated the accuracy and precision of the random variables characterizing the proposed estimators as a function of the SNR. Results indicate a probability of detection close to 1 and show good performance, even for scenarios with a SNR slightly less than -10 dB. The contributions in this work offer enhancements to noise radar capabilities while facilitating improvements in ESM systems.

Sparse Time-Frequency Distribution Reconstruction Using the Adaptive Compressed Sensed Area Optimized with the Multi-Objective Approach.

Compressive sensing (CS) of the signal ambiguity function (AF) and enforcing the sparsity constraint on the resulting signal time-frequency distribution (TFD) has been shown to be an efficient method for time-frequency signal processing. This paper proposes a method for adaptive CS-AF area selection, which extracts the magnitude-significant AF samples through a clustering approach using the density-based spatial clustering algorithm. Moreover, an appropriate criterion for the performance of the method is formalized, i.e., component concentration and preservation, as well as interference suppression, are measured utilizing the information obtained from the short-term and the narrow-band Rényi entropies, while component connectivity is evaluated using the number of regions with continuously-connected samples. The CS-AF area selection and reconstruction algorithm parameters are optimized using an automatic multi-objective meta-heuristic optimization method, minimizing the here-proposed combination of measures as objective functions. Consistent improvement in CS-AF area selection and TFD reconstruction performance has been achieved without requiring a priori knowledge of the input signal for multiple reconstruction algorithms. This was demonstrated for both noisy synthetic and real-life signals.

Frequency Hopping Signal Sorting Algorithm Based on Global Feature of Ambiguity Function

Aiming at the problem that the traditional feature parameters are difficult to meet the fastness and effectiveness of frequency-hopping signal sorting recognition, a feature extraction method based on ambiguity function theory is proposed. The algorithm applies the ambiguity function theory to the frequency hopping signal sorting and identification. Firstly, the ambiguity function of the single-hop signal is calculated, then the AFMR slice of the signal is extracted by the PSO algorithm, and the global features of the AFMR slice are extracted to form the feature vector. The results of FCM clustering experiments show that the extracted feature parameters have higher sorting accuracy and can adapt to the larger dynamic signal-to-noise ratio.

Identification of Frequency Hopping Radiation Sources Based on the Feature of Ambiguity Function

Aiming at the problem that the traditional feature parameters are difficult to meet the fastness and effectiveness of frequency hopping radiation sources identification, a feature extraction method based on radar ambiguity function theory is proposed. The algorithm applies the radar ambiguity function theory to the identification of frequency hopping radiation sources. Firstly, the single pulse ambiguity function of each hop signal is calculated. Then the particle swarm optimization algorithm is used to extract the main ridge slice of ambiguity function of the signal (MRSAF). Based on the noise reduction processing of MRSAF and the stability of MRSAF envelope, the difference sum, difference maximum value and difference distribution entropy characteristics of MRSAF are extracted. The experimental results of fuzzy cluster mean (FCM) show that the extracted feature parameters can be used to identify signals with high accuracy under dynamic SNR conditions.

Training Sequence Design of TDS-OFDM Signal in Joint Radar and Communication System

In the joint radar and communication system, using orthogonal frequency division multiplexing (OFDM) signals, cyclic prefix (CP) and pilots lead to the problem of high peak at the sidelobe (PSL) level in autocorrelation function (ACF), which deteriorates the radar detection performance seriously. To solve this problem, first, a new RadCom signal based on time-domain synchronization OFDM (TDS-OFDM) was proposed. TDS-OFDM adopts training sequence (TS) for guard interval, as well as synchronization and channel estimation, so that CP and pilots can be avoided. And then, ambiguity function (AF) of TDS-OFDM RadCom signal was analyzed. Finally, TS are optimized to suppress PSL of TDS-OFDM signal and maintain the autocorrelation properties of TS simultaneously. The results show that the autocorrelation performance of designed TDS-OFDM RadCom signal is much better than that of CP-OFDM RadCom signal. Considering the importance of radar target detection, TDS-OFDM is more appropriate than CP-OFDM for the RadCom system.

Refining the ambiguity domain characteristics of non-stationary signals for improved time–frequency analysis: Test case of multidirectional and multicomponent piecewise LFM and HFM signals

This paper aims at providing a more accurate description of the ambiguity domain characteristics of a piecewise multicomponent non-stationary signals with focus on piece-wise linear frequency modulated (LFM) (PW-LFM) signal and a mixed LFM and hyperbolic FM (HFM). The main motivation comes from the observed PW-LFM nature of several real life signals. It is essential that the characteristics of these types of signals be taken into account for the design of high resolution Time–Frequency Distributions (TFDs) and therefore to improve the application and interpretation of time–frequency signal analysis and processing. In this paper the ambiguity function (AF) of a general PW-LFM signal is derived exactly and then analyzed to deduce important properties. The precise location and behavior of both auto-terms and cross-terms of a general piecewise LFM signal can be deduced from its AF. Numerical simulations using different types of test signals confirm the analytical derivations. An extension of the PW-LFM test signal is also presented by using HFM signals. For such signals, the exact analytical expression of auto-terms is given as well as the expression of cross-terms between HFM and LFM. The results obtained can be used in future studies to design more advanced quadratic time–frequency distributions (QTFDs) that exhibit improved properties in terms of resolution and accuracy.

A data driven compressive sensing approach for time-frequency signal enhancement

Signals with the time-varying frequency content are generally well represented in the joint time-frequency domain; however, the most commonly used methods for time-frequency distributions (TFDs) calculation generate unwanted artifacts, making the TFDs interpretation more difficult. This downside can be circumvented by compressive sensing (CS) of the signal ambiguity function (AF), followed by the TFD reconstruction based on the sparsity constraint. The most critical step in this approach is a proper CS-AF area selection, with the CS-AF size and shape being generally chosen experimentally, hence decreasing the overall reliability of the method. In this paper, we propose a method for an automatic data driven CS-AF area selection, which removes the need for the user input. The AF samples picked by the here-proposed algorithm ensure the optimal amount of data for the sparse TFD reconstruction, resulting in higher TFD concentration and faster sparse reconstruction algorithm convergence, as shown on examples of both synthetical and real-life signals.

Side Peak Interference Mitigation in FM-Based Passive Radar Via Detection Identification

In frequency-modulation (FM)-based passive radar, the strong side peaks randomly appearing in the ambiguity function will generate a false alarm of target detection. To mitigate this side peak interference, this paper starts with a detailed analysis of the structure and ambiguity function of FM stereo signal. Then, it expounds the formation and characteristics of side peaks, together with a side peak identification method, which identifies and discards the false detections of the same range and Doppler caused by side peaks, respectively. The performance analysis, conducted using both simulated data and real recorded datasets, proves that the proposed method can eliminate the false targets caused by side peaks thus improving the detection performance in FM-passive radar.

Ambiguity function of Inmarsat BGAN signal for radar application

The Inmarsat Broadband Global Area Network (BGAN) L-band downlink signal from a radar viewpoint is studied. The signal is modelled and its ambiguity function (AF) is analysed and the AF is compared with that of the real recorded signal. It is shown that the AF of a single Inmarsat channel has an interference floor of −40 dB for 80 ms integration time. The AF of the Inmarsat BGAN signal is improved by combining multiple frequency channels with channel overlap.

Ambiguity function of Iridium signal for radar application

The Iridium L band downlink signals from a radar viewpoint are studied. The signal is modelled and its ambiguity function is analysed and the ambiguity function with that of the real recorded signal is compared. It is shown that the spectrum and ambiguity diagram of the Iridium signal are independent of the signal content, making it a very suitable signal of opportunity for passive radar. The interference floor of the ambiguity function of a single Iridium burst with a length of 8.28 ms is about 22 dB lower than the main peak.

Analysis of ambiguity function of complicated radiolocation signal with binary phase manipulation by Legendre sequence

Introduction. This article consist calculated ambiguity function, autocorrelation function, cross sections of ambiguity function in different planes. Statement of a problem. Is shown the requirements for the correlation functions of signals used in radiolocation. Method of creating Legandre Sequences. The algorithm of forming sequences Legendre are shown in this article. Shown the advantages of Legendre codes compared with M-sequences. Ambiguity function of Legandre Sequence. The 3D view of ambiguity function of PM signal forming by Legandre Sequence(N=257) is shown in this article. The autocorrelation function of signal is shown. The cross sections of ambiguity function at different layers is submitted. The resolutions of Legandre signal is calculated and compared with resolutions of M-sequences. Conclusion. An analysis of all correlation characteristics of PM signal formed by Legandre-sequence are shown here.

Analysis of autocorrelation and ambiguity function of complicated radiolocation signal with binary phase manipulation by Kasami sequence

Introduction. Were reviewed publications dedicated to pseudorandom sequences in radiolocation, and was made conclusion about necessity of researching in this subject. Modeling of probing radiolocation signal with binary phase manipulation by Kasami sequence. Were considered the method of forming Kasami sequences and measuring their properties. Example of generator for sequence with length 63 symbols is also shown. Technique of research. Were shown graphical results for modeling of Kasami sequence with lengths of 255 binary values. Amplitude of side maximums of autocorrelation function are measured. Modeling of ambiguity function. In this article, graphical results for modeling Kasami sequence ambiguity function are shown. These includes 3-dimensional plot of function body and its cross-sections by plane of equal ranges and planes of function level, equal to 0.9, 0.7, 0.5, 0.4, 0.3, 0.2 and 0.1 of its maximum. Were analyzed amplitude of side maximums, cross-section form and relative values of range and speed resolution. Conclusion. These articles contain analyses of characteristics of previously shown plots. These analyses include estimation of total value of side maximums of ambiguity function of Kasami sequence, ambiguity function cross-section form analysis and conclusion about ability of using these sequences as probe signal in radiolocation.

Parameter Estimation of Co-Channel AIS Signal Using Ambiguity Function

A new data-aided algorithm for parameter estimation of the co-channel AIS signal transmitted over the additive white Gaussian noise channel is proposed in this paper. The co-channel signal consists of a strong signal with high power and a weak signal with low power. The parameters of the strong signal are estimated by searching the ambiguity function of the co-channel signal in two dimensions. A reference signal is therefore reconstructed with the estimated parameters and the aided data. By removing the ambiguity function of the reconstructed reference signal from that of the original co-channel signal, a new co-channel signal ambiguity function is obtained, from which the parameters of the weak signal are estimated. The simulation results illustrate that the proposed algorithm can estimate the parameters of the co-channel AIS signal effectively.

Super-resolution Imaging Realization of Costas Signal

Although the ambiguity function of Costas-coded FH (Frequency Hopping) signal has a thumbtack nature, its resolution in range and velocity domain is constraint by the bandwidth and time duration also. If one target is much stronger than the others in multi-targets detection environment, the sidelobes pedestal will make possible masking via the traditional stretch signal processing. Based on the diffraction model of radar target, sparse decomposition and compressed sensing are applied to reconstruct the radar range-velocity profiles with super-resolution. In order to get the super-resolution profiles, a sparse dictionary is constructed based on the Costas echo model, different sparsity measure functions are studied, and the penalizing function method and the Lagrangian multipliers method are introduced to get the optimal result. Some schemes are introduced to get the optimal atom and the differences between these schemes are compared via simulations. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3904

DVB-T Signal Ambiguity Function Control for Passive Radars

The use of digital video broadcasting-terrestrial (DVB-T) signals as waveform of opportunity for passive coherent location (PCL) is addressed here. The ambiguity function (AF) of the considered waveform of opportunity has been shown to yield regularly spaced undesired peaks which might strongly limit the target detection capability of a DVB-based PCL system. A new technique for DVB-T AF control is proposed, able to overcome the limitations of previously proposed approaches in terms of achievable performance, system requirements, and computational burden. The performance analysis against simulated and real data shows that the proposed technique yields an effective removal of the undesired peaks in the AF thus making the considered waveform more attractive for PCL surveillance.

Ambiguity Function and Resolution Characteristic Analysis of DVB-S Signal for Passive Radar

This paper gives the performance research on the ambiguity function and resolution of passive radar based on DVB-S (Digital Video Broadcasting-Satellite) signal. The radar system structure and signal model of DVB-S signal are firstly studied, then the ambiguity function of DVB-S signal is analyzed. At last, it has been obtained how the bistatic radar position impacts the resolution. Theoretical analyses and computer simulation

Ambiguity function of the radar signal in the synthesis of the 2D radar image of an aircraft

Description of the radar signal ambiguity function for application to the synthesis of the 2D radar image of an aircraft on the basis of spatial frequencies is proposed. Requirements on the time-frequency structure of the sounding signal are determined and the possibility of modeling this signal with the help of a chirp signal is shown.

Feasibility analysis of utilizing the ‘8k mode’ DVB-T signal in passive radar applications

One non-cooperative illuminator recently considered for passive radar applications is the DVB-T (Digital Video Broadcasting-Terrestrial) signal. The thumbtack ambiguity function of the DVB-T signal, in addition to being stationary over time, makes such a signal a good candidate for such applications. However, certain ambiguities in its ambiguity function necessitates certain issues to be carefully considered when the DVB-T signal is to be utilized in these scenarios. Methods have been already proposed to resolve them. In this paper, after studying the origins of these ambiguities, we propose special processing schemes to reduce the complexity of the parts associated with resolving these ambiguities efficiently. Then, the DVB-T’s Cross Ambiguity Function (CAF) processing gain is carefully studied, and it is shown that its noisy nature results in a high processing gain and resolution. Finally, the detection range of the DVB-T based passive radar is examined, besides simulations, to show the practical feasibility of this signal for cases of passive coherent location.

Ambiguity Functions for Monostatic and Bistatic Radar Systems using UWB Throb Signal

Waveform design and ambiguity function are significant tools for the performance analysis of radar systems. We first describe the principle of waveform design for ultrawideband (UWB) impulse waveforms and present the signal model and the advantages of a UWB-throb signal. The ambiguity function of the UWB-throb signal for monostatic radar is derived in detail and analyzed by computer simulation to show its capabilities for enhanced radar performance in terms of target detection, resolution, accuracy of range and velocity measurements, and clutter suppression. The resolution theory for bistatic radar using UWB-throb signal is also presented. The dependence of delay and Doppler shift, associated with a moving target, on the parameters that constitute the geometry of bistatic radar is formulated and used to obtain the bistatic ambiguity function of the UWB-throb signal. Computer simulation plots are generated that clearly illustrate the effects of change in radar-target geometry on the overall characteristics of the bistatic ambiguity function. The computer plots of the monostatic and the bistatic ambiguity functions of the UWB-throb signal demonstrate that such signal can achieve the "thumbtack ambiguity function," that is desirable for the numerous applications of UWB-impulse radar.

Radar Signal Processing Algorithm Using Data Filter

Radar signal processing algorithm is important for radar development, the input data and output data need be analyzed. This paper proposes radar signal processing algorithm using data filter. It creates a data filtering and component based on a finite impulse response filtering approach for use as a general purpose digital filter. It deduces ambiguity function of signal in detail. Experimental results show that the proposed algorithm is effective.