| The skywave over-the-horizon (OTH) radar detects ships and aerial targets over thesea surface, estimates the parameters and tracks these targets by utilizing the reflectedelectromagnetic wave from the ionosphere. The detection range of the skywave OTHradar is not limited by the curvature of the earth, but can detect targets over the seasurface up to800-3500km. Due to this advantage, it has been widely studied andapplied in remote surveillance, early warning, airport surveillance, anti-smuggling andcounter drug, ocean remote sensing, etc.Although the skywave OTH radar has many advantages, it still has manychallenges in target detection especially slow ship target detection due to its complexsignal propagation environment. This dissertation mainly concerns these aspects. Themain research results and contributions include:1. The transient noise has very short duration time but with very strong magnitude.The target spectrum will be masked by the transient noise which makes the targetcannot be detected. On the basis of fully research on the time domain characteristic andfrequency domain characteristic of the transient noise, a transient noise excisionalgorithm based on the S transform is proposed. The algorithm transforms the timedomain return signal onto the time-Doppler domain, which makes the transient noisecan be detected and localized on the two dimensional plane accurately, thus the transientnoise can be excised in time domain effectively.2. The performance of the time domain excision and linear pridiction algorithms isgenerally affected by the linear prediction techniques. In this dissertation, an algorithmbased on the adaptive Gaussian chirplet (AGC) transform is proposed. The algorithmdecomposes the original returned signal into the sum of a series of AGC basis functions,and then the transient noise can be subtracted directly by utilizing the differentcharacteristics between the transient noise and the other signal components in both timeand frequency domains. No linear prediction technique is needed in this algorithm, thusthe adverse effect to the excision can be avoided. Meanwhile, genetic algorithm (GA) isintroduced for the multidimensional search of the AGC basis decomposition.3. For the slow ship target detection, its Doppler frequency is generally close to thefirst-order sea clutter due to its small radial velocity. In order to detect the slow ship target, a relatively long integration time is necessary. The movement of the ionospherewill result in phase noise to the long time integrated returned signal. The noise broadensthe spectrum of the sea clutter and masks the ship target, thus makes the detection moredifficult. The ionospheric effect is generally referred to as the ionospheric contamination.The root cause of the spectrum spread of the sea clutter is the instantaneous frequencyof the clutter changes with each pulse. Taking this into account, an algorithm based onthe complex energy detection (CED) is proposed to estimate the instantaneousfrequency of the clutter and applied to correct the ionospheric contamination.Simulation results show that the proposed algorithm can work and achieve goodperformance in large ionospheric perturbations.For the skywave radar decontamination, based on the cubic phase modeling, a newcubic phase signal instantaneous frequency (IF) estimation algorithm is proposed. Thealgorithm divides the sea clutter into several short data segments, and then estimates theIF of each pulse for the data segments. The final IF of each pulse can be calculated byaveraging the IF of each overlapped data segments. The derived IF is then utilized forthe decontamination. Simulation results show that the IF estimation accuracy is betterthan the Discrete Polynomial phase Transform (DPT) algorithm, and can workeffectively under large ionospheric perturbations.4. For slow ship target, its spectrum generally lies between the two first-orderclutter peaks, and then the target detection is more difficult. Besides the first-orderclutter, the second-order clutter can also influence the detection of the target. Based onthe analysis on the characteristic of the ocean clutter, the covariance matrix of the clutteris firstly decomposed into subspaces. Then the MVDR theory is used to detect the shiptarget. The algorithm can suppress the second-order continuous clutter, thus it can beused to detect the target which lies in between the first-order clutter but not masked.5. For high-speed target, such as aircraft and ballistic missile, target maneuvering isprobably to happen. That is, the aerial target will accelerate during the time duration.For this kind of target, the traditional Range-Doppler processing will lead tosignal-to-noise ratio (SNR) lossing, thus reduce the probability of target detection. Thetarget return signal can be modeled as a polynomial phase signal. Based on this model, anew polynomial phase signal parameter estimation algorithm is proposed. Comparingwith the DPT algorithm, the proposed algorithm can achieve maneuvering targetparameter estimation and movement compensation under lower SNR. Under the specified simulation parameters, when the SNR is3dB, the proposed algorithm obtains5dB or more in the spectrum gain.6. For the aerial target, its flying altitude is also an interested parameter for theskywave radar. For example, the altitude can be used for classifying the aerial targets.Based on the micro-multipath model of the aerial target for the skywave radar, asubspace altitude estimation algorithm is proposed in this dissertation. The algorithmderives the altitude of the target via matching the noise subspace of the observed datawith the signal subspace of the simulated data. The simulation results are presented, andthey show that the proposed algorithm is more robust than the maximum likelihood(ML) algorithm under the specified simulation parameters. |
