Radar target discrimination systems using artificial neural network topology

Claim 3

The method of claim 1 wherein said factors of said multiplying elements corresponding to each of said output signals are coefficients of a bandpass filter for a predetermined one of said frequency components so that the sum signal corresponding to the output signal represents a signal having the amplitude of the frequency component in said combined energy at each of said sample signals.

Claim 4

The method of claim 1 wherein said factors of said multiplying elements corresponding to each of said output signals are coefficients of a discrete Fourier transform for a predetermined one of said frequency components so that the sum signal corresponding to the output signal represents the amplitude of energy present in said combined energy at the frequency component during said predetermined number of said sample signals.

Claim 5

The method of claim 1 wherein said network is a first such network, wherein said output signals thereof are in a first such predetermined form for analysis to detect said predetermined frequency characteristics and wherein the method further comprises: providing a second such network receiving as the input signals thereof said output signals of said first network representing said frequency components in said first predetermined form; selecting said factor of each multiplier element of said second network so that the factors thereof corresponding to each of said output signals of said second network select such a predetermined frequency characteristic in at least one of the input signals of said second network; and selecting a predetermined such activation function for each of said activation elements of said second network so that said activation elements of said second network generate said output signals thereof to represent such a predetermined frequency characteristic in at least one of the input signals of said second network in a second predetermined form for analysis to detect said predetermined frequency characteristics.

Claim 6

The method of claim 4 wherein said predetermined frequency characteristic is a correlation of a plurality of said frequency components represented in said first predetermined form and wherein the method further comprises selecting said factors of each multiplier element corresponding to one of said output signals of said second network as a correlation factor for said frequency characteristic of a plurality of frequency components corresponding to predetermined input signals of said second network representing said frequency components related to one of said frequency components so that said one output signal represents said correlation for said one frequency component.

Claim 7

The method of claim 4 wherein said predetermined frequency characteristic is a variation of said frequency components during a predetermined plurality of said sample signals and wherein the method further comprises: receiving said output signals of said first network in said first predetermined form as a set of initial input signals of said second network; receiving said output signals of said second network as a set of feedback input signals of said second network so that a summing element of said second network and an activation element thereof generate one of said feedback signals; selecting the factors of said multiplier elements corresponding to each initial signal of said set of initial input signals as a predetermined initial factor to provide the initial signal to a predetermined one of said summing elements of said second network; and selecting the factor of each multiplier element corresponding to one of said feedback signals and to the one of said summing elements generating the feedback signal as a predetermined feedback factor to provide the feedback signal to the summing element for summing with the initial signal provided thereto by the corresponding initial factor, each feedback factor being selected in relation to the corresponding initial factor so as to integrate successive such initial input signals over said predetermined plurality of said sample signals.

Claim 8

The method of claim 4 wherein said predetermined frequency characteristic involves the sum of a plurality of said output signals of said first network and wherein the method further comprises selecting said factors of each multiplier element of said second network corresponding to said plurality of said output signals of said first network and to one of said output signals of said second network so that said plurality of output signals are provided to the summing element corresponding to the one output signal of said second network for summing by said summing element, said factors being selected so that the sum signal thereof is within a predetermined range corresponding to the range of one signal of said plurality of output signals of said first network.

Claim 9

The method of claim 2 wherein said network is a first such network and the method further comprises: providing a second such network; providing said sample signals in succession as said input signals of said first network; selecting said factors of said multiplying elements of said first network so that such factors corresponding to a first half of said output signals are said coefficients of said bandpass filter, and so that such factors corresponding to a second half of said output signals are said coefficients of said filter having the same magnitudes as said factors corresponding to said first half of said output signals and being opposite in sign; selecting said activation function of each activation element of said first network to generate an output signal corresponding to zero when said sum signal to the element is below a zero value and corresponding directly to said sum signal when said sum signal is above a zero value, so that said output signals of said first network represent only positive sum signals thereof, and so that each pair of said output signals of said first network corresponding to a pair of said coefficients having the same magnitude and opposite in sign represent the absolute value of said amplitude of such a frequency component; providing said first half of said output signals of said first network as a first set of input signals to said second network; providing said second half of said output signals of said first network as a second set of input signals to said second network; and selecting said factors of said multiplying elements of said second network to provide each first set signal and each second set signal corresponding to the same said frequency component to the summing element corresponding to a predetermined one of said output signals of said second network, said factors of said second network being selected so that such factors corresponding to the same frequency component in said first set and in said second set and also corresponding to one of the output signals of said second network have the same value, such factors of the other multiplying elements corresponding to the one output signal have an effectively zero value, and the sum signal corresponding to the one output signal corresponds to said absolute value, whereby the output signals of the second network correspond to rectified such frequency components.

Claim 10

The method of claim 3 wherein said network is a first such network and the method further comprises approximating a discrete Fourier transform by: providing a second such network; providing said predetermined sample signals as a first set of said input signals of said first network and as a second set of said input signals thereof; selecting said factors of said multiplying elements of said first network so that such factors corresponding to a first half of said output signals are in-phase coefficients of a discrete Fourier transform, such in-phase coefficients corresponding to said second set of input signals having the same magnitudes as such in-phase coefficients corresponding to said first set and being opposite in sign, and such factors corresponding to a second half of said output signals are quadrature coefficients of said discrete Fourier transform for the same frequency components thereof as said first half of said output signals, said quadrature coefficients corresponding to said second set of input signals having the same magnitudes as said quadrature coefficients corresponding to said first set and being opposite in sign; selecting said activation function of each activation element of said first network to generate an output signal corresponding to zero when said sum signal to the element is below a zero value and corresponding directly to said sum signal when said sum signal is above a zero value, so that said output signals of said first network represent only positive sum signals thereof, each pair of said output signals of said first network corresponding to each pair of in-phase coefficients having the same magnitude represent the absolute value of an in-phase frequency component of the discrete Fourier transform, and each pair of said output signals of said first network corresponding to each pair of quadrature coefficients having the same magnitude represent the absolute value of a quadrature frequency component of a discrete Fourier transform; providing said first half of said output signals of said first network as an in-phase set of input signals to said second network; providing said second half of said output signals of said first network as a quadrature set of input signals to said second network; and selecting said factors of said multiplying elements of said second network to provide each in-phase set signal and each quadrature set signal corresponding to the same said frequency component to the summing element corresponding to a predetermined one of said output signals of said second network, said factors of said second network being selected so that such factors corresponding to the same frequency component in said in-phase set and in said quadrature set and also corresponding to one of the output signals of said second network have the same value, such factors of the other multiplying elements corresponding to the one output signal have an effectively zero value, and the sum signal corresponding to the one output signal represents the sum of said absolute values of the in-phase component and the quadrature component, whereby the output signals of the second network correspond to the sum of the absolute values of the in-phase and quadrature components of the frequency components and to said discrete Fourier transform.

Claim 11

The method of claim 1 wherein said activation function is generally sigmoidal.

Claim 12

The method of claim 10 wherein said predetermined form has a first value when said sum signal is below a predetermined threshold and a second value when said sum signal is above said threshold and said activation function is selected as a signum having an asymptotic portion at said first value, a step at said threshold, and another asymptotic portion at said second value.

Claim 13

The method of claim 10 wherein said predetermined form corresponds directly to a predetermined range of said sum signal and said activation function is a sigmoid selected to have a substantially linear central portion disposed at said range.

Claim 14

The method of claim 10 wherein said predetermined form has one value when said sum signal is below a predetermined level and corresponds directly to said sum signal when said sum signal is above said level and said activation function is selected as a sigmoid having an asymptotic portion at said one level and a substantially linear central portion extending from said asymptotic portion.

Claim 15

The method of claim 10 wherein said predetermined form corresponds to a logarithm of a positive said sum signal and said activation function is selected to have a generally logarithmical curved asymptotic portion.