Communications: directive radio wave systems and devices (e.g. – Determining velocity – Combined with determining acceleration
Reexamination Certificate
2000-04-28
2001-11-06
Sotomayor, John B. (Department: 3662)
Communications: directive radio wave systems and devices (e.g.,
Determining velocity
Combined with determining acceleration
C342S109000, C342S115000, C342S192000, C342S196000
Reexamination Certificate
active
06313785
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention involves an improved method and apparatus of signal processing for radar systems. In particular, the present invention pertains to dual path radar signal processing in which high SNR radar return signals are coherently integrated for signal detection and low SNR signals are coherently integrated by fast Fourier transforms and additionally noncoherently integrated for signal detection.
2. State of the Art
Radar systems transmit signals and detect echos reflected from distant target objects to detect the target objects. Detection of a target object includes, for instance, determining the position, direction of movement, velocity and acceleration of target objects. Radar systems typically transmit signals of predetermined frequencies in the form of pulses or waveforms transmitted at varying frequencies. Transmitted radar waveforms of varying frequency can be used to implement linear frequency modulated chirp pulses or some such signal encoding schemes. The transmitted signals can vary in frequency, for example, from the megahertz range up to light wave frequencies in the visible spectrum. Conventional radar systems can have a co-located transmitter and receiver, or can have a transmitter and receiver located at different positions.
Signal strength is important in discerning information about a target object. Because the signal strength of the return signal varies inversely to the fourth power with the distance R between the radar system and the target (1/R
4
), the signal strength of a return signal tends to be weak in comparison to the transmitted signal. In a addition to the distance between the radar system and the target, signal strength and quality are also affected by radar parameters and target variables. Radar aperture, transmit power and amplifier efficiencies are examples of radar parameters which affect a radar system's target detection ability. Likewise, target size, shape, target object material, and target velocity/acceleration, also affect the return signal strength and signal quality. For instance, as target objects, missiles can be especially challenging to detect because they tend to be fast moving, small, targets With a high degree of acceleration uncertainty. In addition, as radar return signals diminish to the level of background noise they tend to be very difficult to detect.
Signal processing can be used to detect weak radar return signals, and to discern the Doppler characteristics of return signals for determining position, velocity and acceleration of the target object. As the signal-to-noise ratio (SNR) decreases, signal processing becomes more important for signal detection. Signal processing also becomes more computationally burdensome as the return signal SNR becomes smaller, since the return signal blends into the background noise. In general, low SNR signals with fewer unknown variables are easier to detect than low SNR signals with more unknown variables. For example, signals having a known acceleration value are easier to detect than signals with an unknown acceleration component.
In order to reduce the unknown variables of return signals and thus enhance signal processing, radar systems typically transmit coherent radar signals. Signal coherence means that the phase is continuous from one transmitted signal to the next, is if the signals were chopped out of the same continuous waveform. Having a known value or expected range of signal phase allows return signals to be more readily manipulated during signal processing and detection. By using coherent signals, radar systems can detect Doppler shifts due to changes in relative velocity between the radar system and the target object.
Signal processing generally involves coherent integration to transform return signals from the time domain to the frequency domain. Typically, a fast Fourier transform (FFT) filter is used for the coherent integration. Signal processing can then be used to analyze the received return signals once they are represented in frequency domain form. However, even for frequency domain analysis, conventional radar systems require that the return signals have sufficient signal strength.
FIG. 1A
is an FFT frequency domain representation of a received signal. The FFT shown in
FIG. 1A
indicates the relative velocity between the radar system and the target object. Target objects with higher velocities relative to the radar system have higher frequencies, and are shown shifted to the right. Target objects moving more slowly relative to the radar system have lower frequencies, and are shown shifted to the left.
By analyzing the FFTs corresponding to different time segments, changes in target velocity can be determined. Detecting target velocity changes within different time segments allows an approximation of acceleration to be made. However, to make such an approximate acceleration determination using a conventional radar signal processor, the received signal must be strong enough for detection in each FFT. If the SNR is too low for target detection of individual FFTs, lo velocity comparison can be made for determining acceleration.
In conventional radar systems, signal processing can be used to detect return signals and determine an unknown target acceleration for return signals characterized by high SNR. Conventional radar systems may also be able to detect the presence of return signals characterized by low SNR, but only if the acceleration component of the return signal is known.
SUMMARY OF THE INVENTION
The Applicants recognize that if acceleration is unknown for low SNR signals, the computational complexity of signal processing becomes much more extensive, to the extent of being beyond the computational capabilities of today's technology. The Applicants identify a drawback of conventional radar systems as being the inability to detect low SNR return signals of unknown acceleration over a wide acceleration range because of the computational burdens of signal processing.
The present invention reduces the computational burdens associated with processing return signals of unknown acceleration and having low SNRs. The present invention provides a more efficient way of performing the operation of noncoherent integration.
Generally speaking, exemplary embodiments are directed to signal processing using a dual path signal processor. Close proximity targets tend to have high SNR values and also tend to have high angular acceleration components. Far away targets tend to have low SNR and lower angular acceleration. The detection of far away, low SNR targets may be achieved by forming a noncoherent FFT array matrix having acceleration bins. But such use of acceleration bins is computationally burdensome. Since close proximity targets tend to be higher in SNR, only the low acceleration, low SNR targets need be detected by using the more extensive processing that employs acceleration bins. The close proximity targets, which tend to have higher SNR values, can be detected within individual FFT templates. By using dual path signal processing according to the present invention, the signal processor detects signals with unknown acceleration components without an unduly burdensome computational load for the signal processor.
The present invention is directed to a signal processing method and system for detecting target objects. According to one embodiment of the signal detection method, electromagnetic signals are received which include target object signals of unknown velocity and acceleration. Target object signals from far away target objects tend to have smaller acceleration components than target object signals from close proximity target objects. The received signals are coherently integrated to transform them from the time domain segments into frequency domain templates of data. The templates are then arranged into an array matrix, and acceleration bins are formed. The acceleration bins can be analyzed to detect the presence of a target object signal. Since formation of acceleration bins requires significant
Burns Doane , Swecker, Mathis LLP
Lockheed Martin Corporation
Sotomayor John B.
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