Low-altitude Target Detection Research Articles

Joint Implementation Method for Clutter Suppression and Coherent Maneuvering Target Detection Based on Sub-Aperture Processing with Airborne Bistatic Radar

An airborne bistatic radar working in downward-looking mode confronts two major challenges for low-altitude target detection. One is range cell migration (RCM) and Doppler migration (DM) resulting from the relative motion of the radar and target. The other is the non-stationarity characteristic of clutter due to the radar configuration. To solve these problems, this paper proposes a joint implementation method based on sub-aperture processing to achieve clutter suppression and coherent maneuvering target detection. Specifically, clutter Doppler compensation and sliding window processing are carried out to realize sub-aperture space–time processing, removing the clutter non-stationarity resulting from the bistatic geometric configuration. Thus, the output matrix of clutter suppression in the sub-aperture could be obtained. Then, the elements with the same phase of this matrix are superimposed and rearranged to achieve the reconstructed 2-D range-pluse echo matrix. Next, the aperture division with respect to slow time is conducted and the RCM correction based on modified location rotation transform (MLRT) and coherent integration (CI) are realized within each sub-aperture. Finally, the matched filtering process (MFP) is applied to compensate for the RCM/DM among different sub-apertures to coherently integrate the maneuvering target energy of all sub-apertures. The simulation and measured data processing results prove the validity of the proposed method.

Research on an Urban Low-Altitude Target Detection Method Based on Image Classification

With the expansion of the civil UAV (Unmanned Aerial Vehicle) market, UAVs are also increasingly being used in illegal activities such as espionage and snooping on privacy. Therefore, how to effectively control the activities of UAVs in cities has become an urgent problem to be solved. Considering the urban background and the radar performance of communication signals, a low-altitude target detection scheme based on 5G base stations is proposed in this paper. A 5G signal is used as the external radiation source, the method of transceiver separation is adopted, and the forward-scattered waves are used to complete the detection of UAV. This paper mainly analyzes the principle of forward scattering detection in an urban environment, where the forward-scattered wave of a target is stronger than the backward-reflected wave and contains both height difference and midline height information on the target. Based on the above theory, this paper proposes a forward-scattered wave recognition algorithm based on YOLOv3-FCWImageNet, which transforms the forward-scattered wave recognition problem into a target detection problem and accomplishes the recognition of forward-scattered waves by using the excellent performance of algorithms in the field of image recognition. Simulation results show that FCWImageNet can distinguish two different low-altitude targets effectively, and realize the monitoring and classification of UAVs.

Low-Altitude Target Detection Method Based on Distributed Sensor Networks

Low-Altitude Target Detection Method Based on Distributed Sensor Networks

Weighted target detector via estimated SNR in a multipath environment

Multipath effect cause serious performance degradation in low-altitude target detection. To overcome the negative multipath effect in a low-altitude environment, a novel weighted detector based on the estimated signal-to-noise ratio (ESNR) is proposed. By introducing the multipath intensity factor, the signal models for different radar systems in the low-altitude environment are established. Then, inspired by the recent development of cognitive theory, the weighted detector based on ESNR is proposed to strengthen the high SNR channels and suppress the low SNR channels. The eigenfunction method is adopted to derive the theoretical detection probability of the proposed detector. Simulation results suggest that, compared with the traditional equal weight detector, the proposed detector can effectively overcome the negative influence of multipath and improve the detection performance in the low-altitude environment. It is also proved that in most cases, with the proposed method, multi-input multi-output (MIMO) radar has better detection performance than that of other radars in the low-SNR region.

Adaptive Two-Step Bayesian Generalized Likelihood Ratio Test Algorithm for Low-Altitude Detection

The low-altitude target detection remains a difficult problem in MIMO radar. In this paper, we propose a novel adaptive two-step Bayesian generalized likelihood ratio test (TB-GLRT) detection algorithm for low-altitude target detection. By defining the compound channel scattering coefficient and applying the K distributed clutter model, the signal models for different radars in low-altitude environment are established. Then, aiming at the problem that the integrals are too complex to yield a closed-form Neyman-Pearson detector, we assume prior knowledge of the channel scattering coefficient and clutter to design an adaptive two-step Bayesian GLRT algorithm for low-altitude target detection. Monte Carlo simulation results verify that the proposed detector has better performance than the square law detector, GLRT detector or Bayesian GLRT detector in low-altitude environment. With the TB-GLRT detector, the maximum detection probability can reach 70% when SNR=0dB and ν=1. Simulations also verify that the multipath effect shows positive influence on detection when SNR<5dB, and when SNR>10dB, the multipath effect shows negative influence on detection. When SNR>0dB, the MIMO radar, which keeps a detection probability over 70% with the proposed algorithm, has the best detection performance. Besides, the detection performance gets improved with the decrease of sea clutter fluctuation level.

OFDM chirp radar for adaptive target detection in low grazing angle

Low-altitude target detection is of great importance in radar applications, especially for military radar to counter the targets penetrated from low grazing angles. However, it is a challenge to detect the targets in low grazing angle area due to severe multipath reflection effects. In this study, the authors propose orthogonal frequency division multiplexing (OFDM) chirp waveform for target detection in low grazing angle region. The OFDM chirp waveform has better peak-to-average-power ratio level and provides larger time-bandwidth product than that of conventional OFDM waveform, which is beneficial for target detection. Two different radar schemes, namely, OFDM chirp radar and OFDM chirp multiple-input multiple-output (MIMO) radar, are studied under the Earth's curvature geometry model with the consideration of realistic multipath reflection effects. The generalised likelihood ratio test algorithm is developed by jointly exploiting the advantages of OFDM chirp waveform and MIMO configuration in increased degrees of freedom. In addition, an adaptive algorithm is further applied to enhance the target detection performance. All proposed schemes are verified by numerical results.

Radio Frequency Interference Suppression Algorithm in Spatial Domain for Compact High-Frequency Radar

High-frequency (HF) ground wave radar is an important tool for sea state measurement and low-altitude target detection. Dense radio frequency interference (RFI) in the HF band inhibits the extraction of sea state parameters and degrades the performance of radar. Though many interference suppression methods based on large arrays have been proposed, most of them are weak to deal with the interference in small-aperture radar. In this letter, a spatial subspace method is proposed to suppress RFI, which uses two crossed-loop/monopole antennas to construct interference subspace at the reserved range bins and projects the echoes onto its orthogonal subspace at the interested range bins. The processed results of measured data from OSMAR-SD verify the high performance of this algorithm for dense RFI suppression. Apart from that, the data utilization ratio and the accuracy of estimating wave height are both improved significantly after the RFI suppression.

Spatial and temporal features selection for low-altitude target detection

Target detection in plane position indicator (PPI) radar images aims at separating moving targets from complicated background image. Background subtraction is a powerful mechanism for such applications. Since there is still much clutter left in the foreground image after background subtraction, an optimal classification plane (OCP) should be constructed to distinguish targets from clutters. Due to the complexity and variability of the foreground and background images, the threshold value of each position of the OCP should be selected adaptively corresponding to each pixel of the foreground image. In this paper, a novel method is proposed to improve the classification results of the OCP with the spatial and temporal features from the PPI radar image sequence. Firstly, to select the thresholds in the OCP adaptively, a new formula is developed with the spatial features from two statistical models. The statistics from the foreground model reflect the aggregation degree of the concerned pixels, while those from the background model reflect their relative positions. Secondly, to further reduce the false alarm rate, a novel strategy based on the temporal features is incorporated to modify the OCP. Our method with the optimal parameter values is compared with the other successful techniques for target detection. Quantitative evaluations show that the proposed method provides better results.

Research of the Earth's Radius Valued Method in Radar Low Altitude Target Detection

Abstract With the development of modern aerospace technology, radar target altitude become lower and lower, so the low-altitude targets quick and accurate location defense system has become urgent to solve. The radar was looking down on the general situation of low altitude targets, if the Earth is considered as a sphere in the wave refraction correction, it will have great error. In this paper, the radar measurement parameters and geodetic coordinate conversion to space coordinate, the calculation method is given with the radar beam radiation at any point corresponding to the Earth's radius.

Low-altitude target detection by coastline operated marine radar

Relevant to a Richian family of fluctuating targets with a composite background of sea-plus-land clutter, the performance prediction of a radar operating in near-coastal regions is elucidated by assuming noncoherent integration of the pulses. Considering the dominance of land clutter, a modified K-distributed statistic is indicated for the overall clutter envelope; and the corresponding probability of false alarm and probability of detection are deduced for fixed threshold detection (s) based on N pulses integrated in the presence of the sea-plus-land clutter and the noise. Even when the target offers a dominant scattered echo, the worst situations of the land clutter affecting the detection performance are indicated. >

Timely prediction of low-altitude radar performance in operational environments using in situ atmospheric refractivity data

A shipboard radar decision aid that may be used to predict current low-altitude radar performance and assist the radar operator in maximising system capabilities in the existing propagation environment is discussed. The system, developed for use aboard US Navy AEGIS-class ships, uses expendable rocketborne radiosondes to make high-resolution measurements of the atmo sphere. A version of the Johns Hopkins University Applied Physics Laboratory&apos;s electromagnetic parabolic equation (EMPE) propagation model is used to calculate the effects of the measured refractivity environment on the propagation of energy radiated by the radar. A radar modeluses these data in predictions of the system&apos;s current low-altitude target detection capabilities. A colour display indicates the size of targets that may be detected through contour shading of a range-height display. The effects of many radar operator controllable options on target detectability may be evaluated in the current propagation environment with this system. A significant portion of the data acquisition-to-display process has been automated. Design and implementation of this system and results of recent at-sea testing are discussed.